Job Description

We are seeking an experienced AI Solutions Architect to design, develop, and implement enterprise-scale Artificial Intelligence solutions that accelerate digital transformation and drive business innovation. The ideal candidate will architect AI platforms leveraging Generative AI, Large Language Models (LLMs), Machine Learning, Retrieval-Augmented Generation (RAG), cloud-native AI services, and modern data platforms.

In this role, you will collaborate with business leaders, data scientists, software engineers, cloud architects, and cybersecurity teams to translate business requirements into secure, scalable, and production-ready AI solutions. You will define AI architecture standards, integrate AI services across enterprise systems, and ensure compliance with Responsible AI and data governance practices.

Key Responsibilities

• Design enterprise AI solution architectures using cloud-native AI platforms.
• Lead the architecture and deployment of Generative AI and LLM-powered applications.
• Develop scalable Retrieval-Augmented Generation (RAG) solutions using vector databases and knowledge repositories.
• Design AI workflows for chatbots, intelligent assistants, document processing, recommendation systems, and predictive analytics.
• Integrate AI solutions with enterprise applications, APIs, databases, and cloud services.
• Select appropriate foundation models, embedding models, and orchestration frameworks for business use cases.
• Define AI governance, security, scalability, and Responsible AI standards.
• Collaborate with Data Engineering teams to build AI-ready data pipelines and feature stores.
• Implement AI model deployment, monitoring, versioning, and lifecycle management using MLOps best practices.
• Optimize AI performance, latency, cost, and inference efficiency.
• Conduct architecture reviews and provide technical leadership across AI initiatives.
• Evaluate emerging AI technologies and recommend enterprise adoption strategies.
• Mentor AI engineers, developers, and solution architects on best practices.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• 8+ years of experience in software engineering, cloud architecture, AI, or machine learning.
• 3+ years of experience designing enterprise AI or Generative AI solutions.
• Strong knowledge of Large Language Models (LLMs), Prompt Engineering, RAG, and AI orchestration frameworks.
• Experience with cloud AI platforms such as Microsoft Azure AI, AWS Bedrock, or Google Vertex AI.
• Proficiency in Python, REST APIs, SQL, and microservices architecture.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Strong understanding of AI security, governance, privacy, and compliance.
• Excellent communication, stakeholder management, and technical leadership skills.

Preferred Skills

• Generative AI
• Large Language Models (LLMs)
• OpenAI GPT Models
• Anthropic Claude
• Google Gemini
• Microsoft Azure AI Foundry
• AWS Bedrock
• Google Vertex AI
• LangChain
• LlamaIndex
• Semantic Kernel
• Hugging Face Transformers
• Vector Databases (Pinecone, Weaviate, Milvus, ChromaDB)
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• Python
• SQL
• Docker
• Kubernetes
• MLflow
• Apache Spark
• Azure Data Factory
• Databricks
• Git
• CI/CD
• Terraform

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
• AWS Certified Machine Learning – Specialty
• AWS Certified Solutions Architect – Professional
• Google Professional Machine Learning Engineer
• Google Professional Cloud Architect
• Databricks Certified Machine Learning Professional
• Kubernetes Certified Application Developer (CKAD)

Benefits

• Competitive salary with annual performance bonus
• Medical, dental, and vision insurance
• Flexible remote and hybrid work options
• Paid vacation and company holidays
• Employee stock purchase program (where applicable)
• Professional certification reimbursement
• Learning and development budget
• Career advancement opportunities in AI and cloud technologies

Job Description

We are seeking a skilled SD-WAN Network Engineer to design, deploy, and manage enterprise Software-Defined Wide Area Network (SD-WAN) solutions across multiple branch offices, data centers, and cloud environments. The ideal candidate will have hands-on experience with Cisco SD-WAN (Viptela), VMware SD-WAN (VeloCloud), Fortinet Secure SD-WAN, Palo Alto Prisma SD-WAN, or Aruba EdgeConnect, along with expertise in routing, switching, network security, and cloud networking.

In this role, you will optimize WAN performance, enhance network reliability, and support digital transformation initiatives by implementing secure, scalable, and automated SD-WAN architectures. You will collaborate with network architects, cloud engineers, and cybersecurity teams to ensure seamless connectivity across hybrid and multi-cloud environments.

Key Responsibilities

• Design, deploy, and maintain enterprise SD-WAN solutions across branch offices and cloud environments.
• Configure and manage SD-WAN edge devices, controllers, and orchestrators.
• Implement dynamic path selection, application-aware routing, and WAN optimization policies.
• Configure VPNs, IPsec tunnels, QoS, traffic shaping, and secure network segmentation.
• Monitor network performance, bandwidth utilization, and application availability using enterprise monitoring tools.
• Troubleshoot complex Layer 2, Layer 3, and SD-WAN connectivity issues.
• Integrate SD-WAN with AWS, Microsoft Azure, Google Cloud Platform (GCP), and SaaS applications.
• Configure routing protocols including BGP, OSPF, EIGRP, and static routing.
• Collaborate with cybersecurity teams to implement Zero Trust Network Access (ZTNA), firewall policies, and secure remote connectivity.
• Automate network configuration and deployment using Python, Ansible, REST APIs, or Terraform.
• Perform software upgrades, firmware updates, and configuration backups.
• Create and maintain network diagrams, architecture documentation, and operational procedures.
• Participate in network disaster recovery planning and business continuity initiatives.
• Provide Tier 3 support and mentor junior network engineers.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Network Engineering, or a related field.
• 4–8+ years of experience in enterprise networking.
• 3+ years of hands-on experience implementing and supporting SD-WAN solutions.
• Strong knowledge of TCP/IP, IPv4/IPv6, LAN/WAN, VLANs, VPNs, QoS, NAT, and MPLS.
• Experience with Cisco Catalyst, Cisco ISR/ASR, Juniper, Aruba, or Fortinet networking devices.
• Experience with cloud networking in AWS, Azure, or GCP.
• Strong troubleshooting and analytical skills.
• Excellent communication and documentation skills.

Preferred Skills

• Cisco SD-WAN (Viptela)
• VMware SD-WAN (VeloCloud)
• Fortinet Secure SD-WAN
• Palo Alto Prisma SD-WAN
• Aruba EdgeConnect
• Cisco DNA Center
• BGP, OSPF, EIGRP
• MPLS
• VPN/IPsec
• QoS
• SD-Access
• VXLAN
• Python
• Ansible
• Terraform
• REST APIs
• AWS Networking
• Azure Virtual WAN
• Linux
• Git
• Wireshark
• SolarWinds
• ThousandEyes

Preferred Certifications

• Cisco Certified Network Professional (CCNP Enterprise)
• Cisco Certified Internetwork Expert (CCIE Enterprise Infrastructure)
• Cisco SD-WAN Specialist Certification
• VMware VCP-NV
• Fortinet NSE 4 or NSE 7
• Palo Alto PCNSE
• AWS Certified Advanced Networking – Specialty
• Microsoft Certified: Azure Network Engineer Associate (AZ-700)

Benefits

• Competitive salary with annual performance bonus
• Medical, dental, and vision insurance
• Flexible remote/hybrid work options
• Paid vacation and company holidays
• Employee stock purchase plan (where applicable)
• Professional certification reimbursement
• Ongoing technical training and career development
• Health and wellness programs

Job Description

We are seeking a highly experienced Senior Power BI Solutions Architect to lead the design, development, and implementation of enterprise-scale Business Intelligence solutions. The ideal candidate will architect modern analytics platforms using Microsoft Power BI, Microsoft Fabric, Azure Synapse Analytics, SQL Server, Azure Data Factory, and Power Platform to deliver secure, scalable, and high-performance reporting solutions.

This role partners closely with business stakeholders, data engineers, cloud architects, and executive leadership to transform complex business requirements into actionable insights through interactive dashboards, semantic models, and enterprise analytics. The successful candidate will establish BI governance, optimize data models, and drive analytics modernization across the organization.

Key Responsibilities

• Design and implement enterprise-scale Power BI architecture and reporting solutions.
• Develop scalable semantic models, reusable datasets, and optimized star schemas.
• Build interactive executive dashboards, KPI scorecards, and self-service analytics solutions.
• Create advanced DAX measures, calculated columns, and Power Query (M) transformations.
• Integrate Power BI with Microsoft Fabric, Azure Synapse Analytics, SQL Server, Azure Data Lake, SharePoint, Dynamics 365, and third-party applications.
• Optimize report performance using DirectQuery, Import, Composite Models, Aggregations, and Incremental Refresh.
• Implement Row-Level Security (RLS), Object-Level Security (OLS), sensitivity labels, and enterprise governance standards.
• Design and manage Power BI workspaces, deployment pipelines, and CI/CD processes using Azure DevOps and Git.
• Collaborate with data engineering teams to develop reliable ETL/ELT pipelines and data warehouse solutions.
• Monitor Power BI Service performance, Premium Capacity utilization, and report usage analytics.
• Establish BI development standards, governance frameworks, documentation, and best practices.
• Mentor Power BI developers, analysts, and junior architects while conducting technical design reviews.
• Support enterprise digital transformation initiatives using Microsoft Fabric, Power Platform, and AI-driven analytics.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Analytics, or a related field.
• 8+ years of experience in Business Intelligence, Data Analytics, or Data Warehousing.
• 5+ years of hands-on experience with Microsoft Power BI.
• Strong expertise in DAX, Power Query (M), SQL, and data modeling.
• Experience with Microsoft Fabric, Azure Synapse Analytics, Azure Data Factory, Azure SQL Database, and Azure Data Lake.
• Strong understanding of dimensional modeling, star schema, snowflake schema, and semantic modeling.
• Experience implementing enterprise security using RLS, OLS, and Azure Active Directory.
• Experience with Power BI Premium, Fabric Capacity, Deployment Pipelines, and workspace administration.
• Knowledge of Power Platform (Power Automate, Power Apps) is preferred.
• Excellent communication, leadership, and stakeholder management skills.

Preferred Skills

• Microsoft Power BI
• Microsoft Fabric
• Azure Synapse Analytics
• Azure Data Factory
• SQL Server
• Azure SQL Database
• Azure Data Lake Storage
• DAX
• Power Query (M)
• Power Platform
• Power Automate
• Power Apps
• Microsoft Entra ID (Azure AD)
• Azure DevOps
• Git
• CI/CD
• Data Warehousing
• ETL/ELT
• Data Governance
• Data Modeling
• REST APIs
• Python (Preferred)

Benefits

• Competitive salary with annual performance bonus
• Medical, dental, and vision insurance
• Flexible remote/hybrid work options
• Paid vacation and holidays
• Professional certification reimbursement
• Microsoft training and learning opportunities
• Career advancement within enterprise data and analytics teams

Job Description

We are seeking an experienced Power BI Solutions Architect to lead the design, architecture, and implementation of enterprise-scale Business Intelligence (BI) solutions using Microsoft Power BI, Microsoft Fabric, Azure Data Services, and the Microsoft Power Platform.

The ideal candidate will work closely with business executives, data engineers, solution architects, and development teams to design scalable analytics platforms that enable self-service reporting, advanced data visualization, and real-time business insights. This role requires deep expertise in BI architecture, data modeling, governance, security, cloud analytics, and enterprise reporting best practices.

As a technical leader, you will define BI standards, optimize enterprise reporting environments, and ensure data quality, performance, security, and scalability across the organization.

Key Responsibilities

• Design and implement enterprise-wide Business Intelligence architecture using Microsoft Power BI and Microsoft Fabric.
• Lead the end-to-end architecture of reporting, analytics, and data visualization solutions.
• Collaborate with business stakeholders to define analytics strategies and reporting roadmaps.
• Design scalable semantic models, data marts, and enterprise data models.
• Develop governance frameworks for Power BI workspaces, datasets, and reports.
• Establish best practices for report development, performance tuning, and deployment.
• Design secure BI solutions using Row-Level Security (RLS), Object-Level Security (OLS), and Microsoft Entra ID integration.
• Architect data integration solutions using Azure Data Factory, Microsoft Fabric, SQL Server, and Azure Synapse Analytics.
• Optimize large-scale Power BI environments for performance, scalability, and high availability.
• Define enterprise KPI frameworks and executive dashboards.
• Mentor Power BI Developers, Data Analysts, and BI Engineers.
• Lead code reviews, architecture reviews, and technical design sessions.
• Implement CI/CD pipelines using Azure DevOps and Git for Power BI deployments.
• Monitor Power BI Service capacity, gateways, refresh schedules, and tenant administration.
• Support executive leadership with enterprise reporting and strategic analytics initiatives.
• Evaluate emerging Microsoft technologies and recommend innovative BI solutions.
• Ensure compliance with data governance, security, privacy, and regulatory standards.

Required Skills

• Microsoft Power BI
• Microsoft Fabric
• Power BI Service Administration
• DAX (Advanced)
• Power Query (M Language)
• Enterprise Data Modeling
• SQL Server
• Azure SQL Database
• Azure Synapse Analytics
• Azure Data Factory
• Azure Data Lake Storage Gen2
• Microsoft Entra ID (Azure AD)
• Row-Level Security (RLS)
• Object-Level Security (OLS)
• Enterprise BI Architecture
• Data Warehousing
• ETL/ELT Design
• Performance Optimization
• Azure DevOps
• Git
• Power Platform
• Power Apps
• Power Automate
• API Integration
• Executive Dashboard Design
• Business Intelligence Strategy
• Cloud Architecture
• Data Governance
• Leadership & Stakeholder Management

Preferred Qualifications

• Bachelor's degree in Computer Science, Information Technology, Data Analytics, Information Systems, or a related field.
• 7–10+ years of experience in Business Intelligence, Data Analytics, or Enterprise Reporting.
• 5+ years of hands-on experience designing enterprise Power BI solutions.
• Strong expertise in Azure cloud services and Microsoft Fabric.
• Experience leading BI architecture for large enterprise environments.
• Experience working with Agile and DevOps methodologies.
• Excellent communication, leadership, and presentation skills.

Preferred Certifications

• Microsoft Certified: Power BI Data Analyst Associate (PL-300)
• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
• Microsoft Certified: Azure Data Engineer Associate (DP-203)
• Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
• Microsoft Certified: Azure Administrator Associate (AZ-104)
• Microsoft Certified: Azure Data Fundamentals (DP-900)
• Microsoft Certified: Power Platform Solution Architect Expert (PL-600)

Preferred Tools & Technologies

• Microsoft Power BI
• Microsoft Fabric
• Power BI Service
• SQL Server
• Azure SQL Database
• Azure Synapse Analytics
• Azure Data Factory
• Azure Data Lake Storage
• Azure DevOps
• GitHub
• Microsoft Entra ID
• Microsoft Purview
• Power Apps
• Power Automate
• SQL Server Management Studio (SSMS)
• Visual Studio Code
• Jira
• Confluence
• SharePoint
• Microsoft Excel
• Python (Basic)
• R (Basic)

Benefits

• Competitive salary with annual performance bonuses
• Medical, Dental, and Vision insurance
• Flexible Remote/Hybrid work model
• Paid Time Off (PTO) and company holidays
• Stock purchase or equity programs (where applicable)
• Certification reimbursement and professional development budget
• Leadership training and career advancement opportunities
• Employee wellness and mental health programs
• Tuition assistance and learning resources

Job Description

We are looking for a Cybersecurity Analyst to protect the organization's networks, systems, applications, and sensitive data from cyber threats. The successful candidate will monitor security events, investigate incidents, assess vulnerabilities, implement security controls, and collaborate with IT teams to strengthen the organization's cybersecurity posture.

The ideal candidate has experience with Security Operations Centers (SOC), SIEM platforms, endpoint security, vulnerability management, and cloud security technologies.

Key Responsibilities

• Monitor security alerts using SIEM platforms such as Microsoft Sentinel, Splunk, or QRadar.
• Analyze security events and investigate potential cyber threats.
• Detect, triage, and respond to cybersecurity incidents.
• Conduct vulnerability assessments and coordinate remediation activities.
• Perform threat analysis and recommend mitigation strategies.
• Monitor endpoint detection and response (EDR) tools.
• Support phishing investigations and email security initiatives.
• Review firewall, IDS/IPS, VPN, and network security logs.
• Collaborate with IT teams to implement security best practices.
• Assist with security audits, compliance assessments, and risk management activities.
• Develop incident response documentation and playbooks.
• Support cloud security monitoring across AWS, Azure, and Google Cloud.
• Create security reports and dashboards for leadership.
• Stay current with emerging cyber threats, attack techniques, and industry trends.

Required Skills

• Security Operations Center (SOC)
• SIEM (Microsoft Sentinel, Splunk, IBM QRadar)
• Incident Response
• Threat Detection
• Vulnerability Assessment
• Endpoint Detection & Response (Microsoft Defender, CrowdStrike)
• Network Security
• TCP/IP
• DNS
• Firewalls
• VPN
• Active Directory
• Microsoft 365 Security
• Cloud Security (AWS, Azure, GCP)
• PowerShell or Python (Basic)
• MITRE ATT&CK Framework
• NIST Cybersecurity Framework
• Risk Assessment
• Analytical & Problem-Solving Skills

Preferred Qualifications

• Bachelor's degree in Cybersecurity, Computer Science, Information Technology, or a related field.
• 2–5 years of cybersecurity or SOC experience.
• Experience with SIEM and EDR platforms.
• Knowledge of Windows, Linux, and cloud environments.
• Familiarity with Zero Trust security architecture.
• Strong written and verbal communication skills.

Preferred Certifications

• CompTIA Security+
• CompTIA CySA+
• GIAC Certified Incident Handler (GCIH)
• GIAC Certified Intrusion Analyst (GCIA)
• Certified Information Systems Security Professional (CISSP)
• Microsoft Certified: Security Operations Analyst (SC-200)
• Microsoft Certified: Cybersecurity Architect Expert (SC-100)
• AWS Certified Security – Specialty
• Certified Ethical Hacker (CEH)

Common Tools & Technologies

• Microsoft Sentinel
• Splunk Enterprise Security
• IBM QRadar
• CrowdStrike Falcon
• Microsoft Defender XDR
• Microsoft Defender for Endpoint
• Palo Alto Cortex XDR
• Tenable Nessus
• Qualys VMDR
• Rapid7 InsightVM
• Microsoft Entra ID
• Okta
• Cisco Secure Firewall
• Palo Alto Networks
• Wireshark
• Burp Suite
• Nmap
• Microsoft Azure
• Amazon Web Services (AWS)
• Google Cloud Platform (GCP)
• Jira
• ServiceNow

Benefits

• Competitive salary with annual bonus
• Medical, Dental, and Vision insurance
• Remote/Hybrid work options
• Paid Time Off (PTO)
• Paid certifications and professional training
• Career advancement opportunities
• Wellness programs
• Employee Assistance Program (EAP)

Job Description

We are seeking a Product Business Analyst to bridge the gap between business stakeholders, customers, and product development teams. In this role, you will analyze business needs, gather and prioritize product requirements, and translate them into detailed functional specifications and user stories. You will work closely with Product Managers, UX/UI Designers, Software Engineers, QA teams, and stakeholders to deliver innovative, customer-focused digital products that align with business objectives.

The ideal candidate has strong analytical skills, experience with Agile methodologies, and a passion for creating data-driven product solutions that enhance user experience and business performance.

Key Responsibilities

• Gather, analyze, and document business and product requirements from internal and external stakeholders.
• Translate business needs into detailed user stories, acceptance criteria, and functional specifications.
• Collaborate with Product Managers to define product vision, roadmap, and feature prioritization.
• Conduct market research, competitor analysis, and customer feedback analysis to identify product opportunities.
• Work closely with UX/UI teams to improve product usability and customer experience.
• Participate in Agile ceremonies, including sprint planning, backlog refinement, daily stand-ups, sprint reviews, and retrospectives.
• Support software development teams by clarifying requirements throughout the development lifecycle.
• Coordinate User Acceptance Testing (UAT) and validate product functionality before release.
• Define and monitor product KPIs, customer engagement metrics, and business outcomes.
• Identify process improvement opportunities to optimize product delivery and operational efficiency.
• Create process flows, wireframes, and business documentation using industry-standard tools.
• Collaborate with engineering, QA, marketing, sales, and customer success teams to ensure successful product launches.
• Support change management and user adoption initiatives for new product features.
• Maintain product documentation and ensure alignment with business goals and compliance requirements.

Required Skills

• Business Analysis
• Product Management Fundamentals
• Agile & Scrum Methodologies
• Requirements Gathering & Documentation
• User Story Writing
• Backlog Management
• Stakeholder Management
• Business Process Modeling (BPMN)
• SQL
• Microsoft Excel (Advanced)
• Jira
• Confluence
• Microsoft Visio or Lucidchart
• Data Analysis
• Product Analytics
• User Acceptance Testing (UAT)
• Communication & Presentation Skills
• Problem Solving & Critical Thinking

Preferred Qualifications

• Bachelor's degree in Business Administration, Information Systems, Computer Science, or a related field.
• 3–7 years of experience as a Product Business Analyst, Business Analyst, or Product Analyst.
• Experience working in Agile/Scrum product development environments.
• Knowledge of SaaS products, cloud platforms, or digital applications.
• Familiarity with Power BI, Tableau, or Google Analytics is a plus.
• Experience with APIs and system integrations is preferred.

Preferred Tools & Technologies

• Jira
• Confluence
• Azure DevOps
• SQL
• Power BI
• Tableau
• Microsoft Excel
• Visio
• Lucidchart
• Figma
• Miro
• Google Analytics
• Postman
• Salesforce
• Microsoft Teams
• Slack

Benefits

• Competitive salary with annual performance bonus
• Medical, Dental, and Vision insurance
• Paid Time Off (PTO) and company holidays
• Flexible remote/hybrid work options
• Professional development and certification reimbursement
• Career advancement opportunities
• Employee wellness programs
• Paid parental leave

Job Summary

We are seeking an experienced AI Governance & Risk Specialist to establish and manage governance, risk, and compliance frameworks for Artificial Intelligence (AI) systems across the enterprise. In this role, you will work closely with AI Engineers, Data Scientists, Security, Legal, Privacy, Compliance, and Product teams to ensure AI solutions are developed and deployed responsibly, securely, and in accordance with regulatory and organizational requirements. The ideal candidate has expertise in AI governance, enterprise risk management, regulatory compliance, cybersecurity, and Responsible AI principles.

Key Responsibilities

• Develop and maintain enterprise AI governance frameworks, policies, standards, and procedures.
• Conduct AI risk assessments across machine learning models, Generative AI applications, and Large Language Models (LLMs).
• Evaluate AI systems for fairness, bias, explainability, transparency, privacy, and security risks.
• Ensure compliance with applicable AI regulations, privacy laws, and industry standards.
• Establish AI risk registers, governance committees, and approval workflows.
• Perform AI impact assessments before production deployments.
• Collaborate with Legal, Security, Compliance, Privacy, Data Science, and Engineering teams on AI governance initiatives.
• Monitor AI systems for ongoing compliance, performance, and operational risk.
• Support internal and external audits related to AI governance and regulatory compliance.
• Prepare executive reports, dashboards, and risk assessments for senior leadership.
• Track emerging AI regulations and recommend governance improvements.

Required Qualifications

• Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Data Science, Risk Management, or a related field.
• 5–8+ years of experience in Governance, Risk & Compliance (GRC), Cybersecurity, Enterprise Risk, or AI Governance.
• Experience implementing governance frameworks for AI or machine learning systems.
• Strong understanding of AI lifecycle, machine learning concepts, and Generative AI technologies.
• Knowledge of enterprise risk management, cybersecurity, and regulatory compliance.
• Excellent analytical, communication, and stakeholder management skills.

Preferred Skills

• AI Governance
• Responsible AI
• Enterprise Risk Management
• AI Risk Assessments
• Generative AI
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• AI Model Governance
• AI Security
• Privacy & Data Protection
• Regulatory Compliance
• Third-Party Risk Management
• Cloud Security Governance
• Audit & Compliance

Technical Skills

• NIST AI Risk Management Framework (AI RMF)
• ISO/IEC 42001 (AI Management Systems)
• ISO/IEC 23894 (AI Risk Management)
• ISO 27001
• NIST Cybersecurity Framework (CSF)
• SOC 2
• GDPR
• HIPAA
• PCI DSS
• COBIT
• ServiceNow Integrated Risk Management (IRM)
• Archer GRC
• OneTrust
• Microsoft Purview
• Azure AI Foundry
• AWS AI Services
• Google Cloud Vertex AI
• Power BI
• SQL (preferred)
• Python (basic scripting for automation is a plus)

Benefits

• Competitive salary with annual performance bonus.
• Medical, dental, and vision insurance.
• Paid vacation, holidays, and parental leave.
• Flexible remote and hybrid work options.
• Employee stock purchase plan or equity (where applicable).
• Professional development budget for certifications and conferences.

Job Summary

We are seeking a highly skilled Senior AI Data Scientist to lead the design, development, and deployment of advanced Artificial Intelligence (AI) and Machine Learning (ML) solutions. In this role, you will work with large-scale datasets, build predictive models, develop Generative AI applications, and collaborate with cross-functional teams to solve complex business challenges. The ideal candidate has strong expertise in data science, deep learning, Large Language Models (LLMs), statistical modeling, and cloud-based AI platforms.

Key Responsibilities

• Design, develop, and deploy machine learning and deep learning models for production environments.
• Build predictive analytics, recommendation systems, forecasting models, and AI-powered decision support solutions.
• Develop and optimize Generative AI applications using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
• Analyze structured and unstructured data to identify trends, patterns, and business opportunities.
• Perform feature engineering, data preprocessing, and model optimization.
• Fine-tune foundation models and evaluate model accuracy, precision, recall, and performance.
• Build scalable AI pipelines using Python and cloud-native technologies.
• Collaborate with Data Engineers, Software Engineers, Product Managers, and business stakeholders to deliver AI-driven solutions.
• Monitor deployed models for performance, bias, drift, and reliability.
• Mentor junior Data Scientists and provide technical leadership on AI initiatives.
• Communicate complex analytical findings to technical and non-technical audiences.
• Stay current with emerging AI technologies, research, and industry best practices.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field (Ph.D. preferred for research-focused roles).
• 5–8+ years of experience in Data Science, Machine Learning, or Artificial Intelligence.
• Strong programming skills in Python, SQL, and data analysis libraries.
• Experience developing and deploying production-grade AI/ML models.
• Hands-on experience with supervised and unsupervised learning techniques.
• Strong understanding of statistical analysis, probability, and predictive modeling.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud.
• Excellent problem-solving, communication, and leadership skills.

Preferred Skills

• Generative AI
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• LangChain or LangGraph
• Hugging Face Transformers
• Vector Databases (Pinecone, FAISS, ChromaDB)
• MLOps (MLflow, Kubeflow)
• Docker & Kubernetes
• Apache Spark
• AI Model Monitoring
• Responsible AI and AI Governance

Technical Skills

• Python
• SQL
• Pandas
• NumPy
• Scikit-learn
• TensorFlow
• PyTorch
• XGBoost
• LightGBM
• Hugging Face
• OpenAI API
• LangChain
• MLflow
• Apache Spark
• Databricks
• Docker
• Kubernetes
• Git & GitHub
• AWS SageMaker / Azure Machine Learning / Google Vertex AI
• Power BI or Tableau

Preferred Industry Experience

• Artificial Intelligence
• Financial Services
• Healthcare
• Cybersecurity
• Retail & E-commerce
• Manufacturing
• Telecommunications
• Cloud Computing
• Autonomous Systems

Benefits

• Competitive salary with annual performance bonus.
• Medical, dental, and vision insurance.
• Paid vacation, holidays, and parental leave.
• Flexible remote and hybrid work options.
• Employee stock purchase plan or equity (where applicable).
• Learning and development budget for AI certifications and conferences.

Job Summary

We are looking for a skilled AI Automation QA Engineer to design, develop, and maintain automated testing solutions for AI-powered applications, machine learning models, and Generative AI systems. In this role, you will collaborate with AI Engineers, Software Developers, Data Scientists, and DevOps teams to ensure AI applications are reliable, scalable, secure, and production-ready. The ideal candidate has strong experience in automation testing, API validation, CI/CD pipelines, and testing AI-driven products such as LLMs, chatbots, recommendation engines, and intelligent automation platforms.

Key Responsibilities

• Design and implement automated test frameworks for AI and machine learning applications.
• Develop and maintain UI, API, regression, integration, and end-to-end automated test suites.
• Validate AI model outputs for accuracy, consistency, reliability, and performance.
• Test Large Language Models (LLMs), AI copilots, chatbots, and Retrieval-Augmented Generation (RAG) applications.
• Create automated test scripts using Python, Selenium, Playwright, or similar frameworks.
• Automate API testing using REST Assured, Postman, or similar tools.
• Integrate automated testing into CI/CD pipelines using Jenkins, GitHub Actions, or Azure DevOps.
• Monitor AI application performance, identify defects, and collaborate with development teams to resolve issues.
• Validate training datasets, model deployments, and inference pipelines.
• Conduct performance, load, security, and compatibility testing for AI applications.
• Generate detailed test reports, defect documentation, and quality metrics.
• Support continuous improvement of QA processes and automation frameworks.

Required Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field.
• 3–6 years of experience in QA Automation or Software Testing.
• Experience testing AI/ML or Generative AI applications is highly preferred.
• Strong programming skills in Python, Java, or JavaScript.
• Hands-on experience with Selenium, Playwright, Cypress, or similar automation frameworks.
• Experience with REST API testing and API automation.
• Knowledge of software development lifecycle (SDLC) and Agile methodologies.
• Familiarity with machine learning concepts and AI workflows.
• Experience with Git, Docker, Kubernetes, and CI/CD tools.
• Excellent analytical, problem-solving, and communication skills.

Preferred Skills

• Large Language Models (LLMs)
• Prompt Engineering
• LangChain or LangGraph
• Retrieval-Augmented Generation (RAG)
• OpenAI APIs or similar AI platforms
• Vector Databases (Pinecone, FAISS, ChromaDB)
• SQL and NoSQL databases
• Jenkins, GitHub Actions, Azure DevOps
• AWS, Azure, or Google Cloud Platform
• Performance testing tools (JMeter, k6)
• AI model evaluation and Responsible AI principles

Technical Skills

• Python
• Selenium
• Playwright
• PyTest
• REST API Testing
• Postman
• SQL
• Git & GitHub
• Jenkins
• Docker
• Kubernetes
• Azure DevOps
• AWS / Azure / GCP
• LangChain
• OpenAI API
• JMeter
• Machine Learning Fundamentals

Benefits

• Competitive salary with annual performance bonus.
• Medical, dental, and vision insurance.
• Paid vacation, holidays, and parental leave.
• Flexible remote or hybrid work options.
• Professional development and AI certification reimbursement.
• Stock options or equity (company-dependent).
• Career growth opportunities in AI Engineering and Automation.

Job Description

We are seeking an experienced Principal AI QA Engineer to lead the quality strategy for enterprise Artificial Intelligence products, including Large Language Models (LLMs), Generative AI applications, AI agents, Retrieval-Augmented Generation (RAG) systems, and machine learning platforms. As a technical leader, you will define AI testing standards, develop scalable quality frameworks, and ensure AI solutions meet the highest levels of accuracy, reliability, safety, performance, and regulatory compliance.

In this role, you will work closely with AI researchers, machine learning engineers, software developers, product managers, MLOps engineers, and security teams to establish end-to-end quality assurance processes throughout the AI development lifecycle. You will drive automation, benchmark model performance, evaluate AI outputs, and lead initiatives to improve the robustness and trustworthiness of production AI systems.

The ideal candidate has deep expertise in software quality engineering, AI testing methodologies, test automation, cloud-native technologies, and modern Generative AI platforms.

Key Responsibilities

• Define and lead the enterprise AI Quality Assurance strategy across multiple AI products and platforms.
• Design and implement comprehensive testing frameworks for Large Language Models (LLMs), Generative AI applications, AI agents, and machine learning systems.
• Develop automated validation pipelines to evaluate model accuracy, consistency, robustness, fairness, and reliability.
• Lead functional, regression, integration, API, performance, security, and end-to-end testing for AI-powered applications.
• Design evaluation methodologies for prompt engineering, prompt optimization, and LLM response quality.
• Create benchmark datasets and automated scoring frameworks to measure AI model performance.
• Validate Retrieval-Augmented Generation (RAG) pipelines, vector search quality, and knowledge retrieval accuracy.
• Conduct adversarial testing to identify hallucinations, prompt injection vulnerabilities, jailbreak attempts, unsafe outputs, and model weaknesses.
• Monitor production AI systems for model drift, latency, reliability, inference quality, and operational health.
• Establish AI quality metrics, testing standards, governance processes, and release criteria.
• Collaborate with cross-functional engineering teams to resolve quality issues and improve AI system performance.
• Mentor QA engineers and promote best practices in AI quality engineering and test automation.
• Support Responsible AI initiatives by evaluating bias, fairness, explainability, privacy, and compliance requirements.
• Analyze production incidents, perform root cause analysis, and implement preventive quality improvements.
• Drive continuous improvement of AI testing frameworks, automation coverage, and engineering processes.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, or a related technical field.
• 8+ years of experience in Software Quality Assurance, Test Automation, or Quality Engineering.
• 4+ years of hands-on experience testing AI, Machine Learning, or Generative AI systems.
• Strong experience with Large Language Models (LLMs), AI agents, and enterprise AI platforms.
• Advanced programming skills in Python and experience developing automated testing frameworks.
• Experience with RESTful API testing, automation tools, and CI/CD pipelines.
• Strong understanding of machine learning concepts, model evaluation, and AI validation techniques.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Excellent analytical, problem-solving, leadership, and communication skills.

Preferred Qualifications

• Experience evaluating GPT-based models, Claude, Gemini, Llama, or other foundation models.
• Knowledge of Prompt Engineering and prompt evaluation techniques.
• Experience testing Retrieval-Augmented Generation (RAG) applications.
• Familiarity with vector databases and semantic search technologies.
• Experience with Docker, Kubernetes, and MLOps workflows.
• Knowledge of Responsible AI, AI governance, and model risk management.
• Experience performing AI security testing and adversarial evaluations.

Technical Skills

Programming & Scripting

• Python
• SQL
• Java
• JavaScript
• Bash

AI & Machine Learning

• Large Language Models (LLMs)
• Generative AI
• Retrieval-Augmented Generation (RAG)
• AI Agents
• Prompt Engineering
• Machine Learning
• Model Evaluation
• AI Benchmarking
• Responsible AI
• AI Safety Testing

Testing & Automation

• AI Model Validation
• Functional Testing
• Regression Testing
• Integration Testing
• Performance Testing
• Security Testing
• API Testing
• Test Automation
• End-to-End Testing

Tools & Platforms

• PyTest
• Playwright
• Selenium
• Postman
• JMeter
• Jenkins
• GitHub Actions
• Git
• Docker
• Kubernetes

Cloud Technologies

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Preferred Certifications

• ISTQB Advanced Test Automation Engineer
• AWS Certified Machine Learning – Specialty
• Microsoft Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• Certified Kubernetes Application Developer (CKAD)

Benefits

• Annual performance bonus and potential equity/stock awards.
• Comprehensive medical, dental, and vision insurance.
• Flexible paid time off and company holidays.
• Remote and hybrid work opportunities.
• Professional development and certification reimbursement.
• Wellness and employee assistance programs.
• Paid parental leave.

Job Summary

We are seeking an experienced Principal Business Analytics Consultant to lead enterprise-wide analytics initiatives and help clients solve complex business challenges through data-driven strategies. In this role, you will partner with executive stakeholders to define business objectives, develop analytics roadmaps, and deliver innovative solutions that improve operational efficiency, customer experience, and financial performance.

As a senior leader, you will oversee large-scale consulting engagements, mentor analytics teams, and drive digital transformation initiatives using advanced analytics, artificial intelligence (AI), machine learning (ML), and modern business intelligence platforms. The ideal candidate combines deep analytical expertise with exceptional business acumen and executive communication skills.

Key Responsibilities

• Lead strategic business analytics and digital transformation engagements for enterprise clients.
• Partner with C-suite executives and business leaders to define analytics strategies aligned with organizational goals.
• Design and implement enterprise analytics frameworks, KPIs, and performance measurement systems.
• Analyze complex business data to identify trends, risks, and opportunities for growth.
• Develop executive dashboards, scorecards, and self-service reporting solutions using Power BI, Tableau, or Looker.
• Build predictive models, forecasting solutions, and scenario analyses to support strategic planning.
• Advise clients on analytics modernization, cloud migration, and AI adoption.
• Collaborate with cross-functional teams including Data Engineering, Data Science, Finance, Marketing, Operations, and IT.
• Oversee data governance, data quality, and business intelligence best practices.
• Present actionable recommendations and business cases to executive leadership and client stakeholders.
• Lead workshops, stakeholder interviews, and requirements-gathering sessions.
• Mentor and coach consultants, analysts, and project teams to foster technical and professional growth.
• Support business development by contributing to proposals, solution designs, and client presentations.
• Stay informed about emerging trends in business analytics, AI, automation, and cloud technologies.

Required Qualifications

• Bachelor's degree in Business Analytics, Data Analytics, Computer Science, Information Systems, Economics, Finance, Statistics, or a related field.
• 10+ years of experience in business analytics, business intelligence, management consulting, or enterprise data strategy.
• Demonstrated experience leading large-scale analytics or digital transformation initiatives.
• Advanced proficiency in SQL and data analysis techniques.
• Expertise with business intelligence platforms such as Power BI, Tableau, or Looker.
• Strong understanding of data modeling, data warehousing, and enterprise reporting.
• Experience with cloud data platforms such as Snowflake, Databricks, Amazon Redshift, Google BigQuery, or Azure Synapse Analytics.
• Knowledge of ETL/ELT processes and modern data integration tools.
• Excellent executive communication, presentation, and stakeholder management skills.
• Proven ability to lead cross-functional teams and influence strategic decision-making.

Preferred Qualifications

• Master's degree (MBA, Business Analytics, Data Science, Information Systems, or a related field).
• Experience with AI, machine learning, and predictive analytics initiatives.
• Familiarity with Python or R for advanced analytics.
• Consulting experience at a global professional services firm or enterprise technology company.
• Professional certifications in cloud platforms, business intelligence, or project management (e.g., Microsoft Power BI, AWS, Azure, Google Cloud, PMP).

Technical Skills

Analytics & Business Intelligence

• Power BI
• Tableau
• Looker
• Microsoft Excel (Advanced)
• DAX
• Power Query (M)

Programming & Query Languages

• SQL
• Python
• R

Cloud & Data Platforms

• Snowflake
• Databricks
• Amazon Redshift
• Google BigQuery
• Azure Synapse Analytics
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Data Engineering & Integration

• dbt
• Azure Data Factory
• Informatica
• Talend
• Apache Spark (preferred)

Consulting & Strategy

• Business Process Improvement
• KPI Design
• Executive Reporting
• Digital Transformation
• Data Governance
• Financial & Operational Analytics
• Predictive Analytics
• Change Management

Soft Skills

• Executive communication
• Strategic thinking
• Leadership and team development
• Client relationship management
• Problem-solving and critical thinking
• Negotiation and influence
• Decision-making
• Business storytelling with data
• Project and stakeholder management
• Collaboration across global teams

Compensation & Benefits

• Annual performance bonus (15–30%)
• Equity/RSUs (where applicable)
• Medical, dental, and vision insurance
• 401(k) retirement plan with employer match
• Flexible remote or hybrid work options
• Generous paid time off and company holidays
• Professional development and certification reimbursement
• Employee wellness and mental health programs
• Leadership development opportunities

Job Summary

We are seeking a highly analytical and detail-oriented Senior Business Intelligence Analyst to join our growing Data & Analytics team. In this role, you will transform complex datasets into actionable business insights that support strategic decision-making across the organization. You will collaborate with cross-functional teams—including Finance, Sales, Marketing, Product, Operations, and Executive Leadership—to design scalable reporting solutions, develop interactive dashboards, and deliver meaningful analytics that drive business performance.

The ideal candidate has strong expertise in SQL, data modeling, business intelligence tools such as Power BI or Tableau, and data visualization best practices. Experience with cloud data platforms, ETL processes, and stakeholder management is highly valued.

Key Responsibilities

• Design, build, and maintain executive dashboards and KPI scorecards using Power BI, Tableau, or similar BI tools.
• Develop complex SQL queries to extract, clean, and analyze large datasets from multiple data sources.
• Analyze business trends, customer behavior, operational performance, and financial metrics to identify opportunities for improvement.
• Partner with stakeholders across departments to gather reporting requirements and translate business needs into scalable BI solutions.
• Develop automated reporting processes that improve efficiency and reduce manual effort.
• Create and maintain data models, semantic layers, and reporting datasets for enterprise-wide analytics.
• Perform data validation and quality assurance to ensure reporting accuracy and consistency.
• Identify trends, anomalies, and actionable insights through exploratory data analysis.
• Build forecasting and performance measurement models to support strategic planning.
• Present analytical findings and recommendations to senior leadership in a clear and concise manner.
• Collaborate with Data Engineering teams to optimize data pipelines and warehouse performance.
• Support self-service analytics initiatives by enabling business users with intuitive reporting solutions.
• Establish and document BI standards, reporting methodologies, and best practices.
• Monitor dashboard performance and implement enhancements based on user feedback.
• Stay current with emerging BI technologies, analytics tools, and industry trends.

Required Qualifications

• Bachelor's degree in Business Analytics, Data Analytics, Computer Science, Information Systems, Statistics, Mathematics, Economics, Finance, or a related field.
• 5–8+ years of experience in Business Intelligence, Data Analytics, or Business Analytics.
• Advanced proficiency in SQL for querying and manipulating large datasets.
• Hands-on experience with Power BI, Tableau, Looker, or similar business intelligence platforms.
• Strong understanding of data modeling concepts, relational databases, and data warehousing.
• Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
• Knowledge of ETL processes and data integration techniques.
• Strong analytical, problem-solving, and critical-thinking skills.
• Excellent communication and presentation skills with the ability to explain technical concepts to non-technical audiences.
• Experience working in Agile or Scrum environments.

Preferred Qualifications

• Master's degree in Business Analytics, Data Science, Information Systems, or a related field.
• Experience with Python or R for data analysis and automation.
• Knowledge of data governance and master data management practices.
• Experience with Snowflake, Databricks, Redshift, BigQuery, or Azure Synapse.
• Familiarity with version control tools such as Git.
• Experience building predictive analytics or forecasting models.
• BI platform certifications (e.g., Microsoft Power BI Data Analyst Associate or Tableau Certified Data Analyst).

Technical Skills

Business Intelligence Tools

• Power BI
• Tableau
• Looker
• Qlik Sense
• SAP BusinessObjects

Programming & Query Languages

• SQL
• Python
• R
• DAX
• Power Query (M)

Databases & Data Warehousing

• SQL Server
• PostgreSQL
• MySQL
• Oracle
• Snowflake
• Amazon Redshift
• Google BigQuery
• Azure Synapse Analytics

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

Data Integration & ETL

• SQL Server Integration Services (SSIS)
• Azure Data Factory
• Informatica
• Talend
• dbt

Analytics & Reporting

• KPI Development
• Data Visualization
• Forecasting
• Trend Analysis
• Financial Reporting
• Customer Analytics
• Operational Analytics

Collaboration Tools

• Jira
• Confluence
• Microsoft Teams
• Slack

Soft Skills

• Analytical thinking
• Strategic problem-solving
• Stakeholder management
• Business acumen
• Effective communication
• Data storytelling
• Leadership and mentoring
• Collaboration
• Time management
• Attention to detail
• Adaptability
• Decision-making

Career Progression

• Business Intelligence Analyst
• Senior Business Intelligence Analyst
• Lead Business Intelligence Analyst
• Business Intelligence Manager
• Analytics Manager
• Director of Business Intelligence
• Director of Analytics
• Head of Business Intelligence
• Vice President of Analytics
• Chief Data & Analytics Officer (CDAO)

Why Join Us

• Competitive salary and performance-based bonuses.
• Comprehensive medical, dental, and vision insurance.
• Flexible remote or hybrid work options.
• Paid time off, company holidays, and wellness programs.
• Professional development and certification reimbursement.
• Access to cutting-edge analytics tools and cloud technologies.
• Collaborative, data-driven culture with opportunities for career growth.
• Opportunity to influence strategic business decisions through data and analytics.

Job Summary

We are seeking an experienced AI Ethics Specialist to help ensure that our Artificial Intelligence systems are developed and deployed responsibly, ethically, and in compliance with global regulations. In this role, you will collaborate with AI engineers, data scientists, legal teams, product managers, and cybersecurity professionals to identify ethical risks, establish governance frameworks, and promote fairness, transparency, accountability, and privacy across AI initiatives.

The ideal candidate has experience in Responsible AI, AI governance, risk management, algorithmic fairness, and emerging AI regulations, with a strong understanding of machine learning and Generative AI technologies.

Key Responsibilities

• Develop and implement Responsible AI policies, standards, and governance frameworks.
• Evaluate AI systems for fairness, transparency, explainability, bias, and accountability.
• Conduct AI ethics impact assessments and risk analyses for machine learning and Generative AI projects.
• Collaborate with AI development teams to integrate ethical principles throughout the AI lifecycle.
• Monitor compliance with global AI regulations and industry standards.
• Identify and mitigate algorithmic bias, discrimination, and unintended AI outcomes.
• Develop AI governance documentation, ethical guidelines, and best practices.
• Support internal AI ethics review boards and governance committees.
• Work with legal, privacy, compliance, and cybersecurity teams to address AI-related risks.
• Educate employees on Responsible AI principles through workshops and training sessions.
• Stay informed about emerging AI technologies, regulatory developments, and ethical challenges.
• Prepare reports and recommendations for executive leadership regarding AI governance and compliance.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Law, Ethics, Public Policy, or a related field.
• 4–8+ years of experience in AI Governance, Responsible AI, AI Risk Management, Data Ethics, or Technology Compliance.
• Understanding of machine learning, Generative AI, and Large Language Models (LLMs).
• Knowledge of AI fairness, explainability, accountability, transparency, and privacy principles.
• Familiarity with AI governance frameworks and international standards.
• Strong analytical, problem-solving, communication, and stakeholder management skills.
• Experience working with cross-functional technical and business teams.

Preferred Qualifications

• Experience implementing Responsible AI programs in enterprise environments.
• Knowledge of AI risk management frameworks such as the NIST AI Risk Management Framework (AI RMF).
• Familiarity with ISO/IEC 42001, ISO/IEC 23894, and other AI governance standards.
• Experience conducting AI model audits and algorithmic impact assessments.
• Understanding of data privacy regulations, including GDPR, CCPA, and HIPAA.
• Experience with AI model documentation, model cards, and governance reporting.
• Background in cybersecurity governance or enterprise risk management is a plus.

Technical Skills

AI & Machine Learning

• Machine Learning Fundamentals
• Generative AI
• Large Language Models (LLMs)
• Explainable AI (XAI)
• AI Model Evaluation
• Responsible AI Principles

Governance & Compliance

• NIST AI Risk Management Framework (AI RMF)
• ISO/IEC 42001 (AI Management Systems)
• ISO/IEC 23894 (AI Risk Management)
• GDPR
• CCPA
• HIPAA
• SOC 2
• ISO 27001

Programming & Data

• Python (preferred)
• SQL
• Jupyter Notebook
• Git
• Data Analysis

AI Platforms & Tools

• OpenAI API
• Azure AI
• AWS AI Services
• Google Vertex AI
• Hugging Face
• IBM watsonx

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• Certified Information Systems Security Professional (CISSP)
• Certified Information Privacy Professional (CIPP)
• ISO/IEC 42001 Lead Implementer
• ISO/IEC 27001 Lead Implementer
• NIST AI Risk Management Framework Training
• Google Professional Machine Learning Engineer (Preferred)

Benefits

• Competitive salary with annual performance bonuses
• Medical, dental, and vision insurance
• Paid vacation, holidays, and parental leave
• Flexible hybrid work environment
• Professional development and certification reimbursement
• Access to enterprise AI research and innovation programs
• Career growth opportunities in AI Governance, Responsible AI, and AI Strategy

Job Summary

We are seeking an experienced Applied AI & Machine Learning Scientist to develop and deploy cutting-edge artificial intelligence and machine learning solutions that solve complex business and engineering challenges. In this role, you will research, build, and optimize predictive models, deep learning systems, and Generative AI applications while collaborating with software engineers, data scientists, and product teams. The ideal candidate is passionate about AI innovation and has hands-on experience delivering production-ready machine learning solutions at scale.

Key Responsibilities

• Design, develop, and deploy machine learning and deep learning models for production environments.
• Build AI-powered applications using supervised, unsupervised, and reinforcement learning techniques.
• Develop and optimize Large Language Model (LLM) and Generative AI solutions.
• Perform data preprocessing, feature engineering, and exploratory data analysis.
• Train, evaluate, and fine-tune machine learning models to improve performance and accuracy.
• Collaborate with Data Engineers and MLOps teams to build scalable AI pipelines.
• Deploy AI models using cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Monitor model performance and implement continuous improvements.
• Conduct research on emerging AI technologies and evaluate their business applications.
• Develop recommendation systems, predictive analytics, computer vision, or natural language processing (NLP) solutions.
• Document AI models, experiments, and technical processes.
• Follow Responsible AI, data privacy, and model governance best practices.

Required Qualifications

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or a related field (Bachelor's degree with equivalent industry experience may also be considered).
• 4–8+ years of experience in Machine Learning, Artificial Intelligence, or Data Science.
• Strong programming skills in Python and SQL.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.
• Strong understanding of statistics, probability, optimization, and predictive modeling.
• Experience deploying machine learning models into production environments.
• Familiarity with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Large Language Models (LLMs) and Generative AI technologies.
• Hands-on experience with Retrieval-Augmented Generation (RAG), vector databases, and prompt engineering.
• Experience with NLP, computer vision, recommendation systems, or time-series forecasting.
• Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.
• Experience with distributed computing frameworks such as Apache Spark or Ray.
• Publications or contributions to AI research or open-source machine learning projects are a plus.

Technical Skills

• Programming: Python, SQL, R
• Machine Learning: Scikit-learn, XGBoost, LightGBM
• Deep Learning: TensorFlow, PyTorch, Keras
• Generative AI: OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex
• Large Language Models: GPT, Llama, Mistral, Gemini
• Data Processing: Pandas, NumPy, Apache Spark
• Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform (GCP)
• MLOps: MLflow, Kubeflow, Docker, Kubernetes
• Visualization: Tableau, Power BI, Matplotlib
• Version Control: Git, GitHub

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• Google Professional Machine Learning Engineer
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certificate

Benefits

• Competitive salary with annual performance bonuses
• Medical, dental, and vision insurance
• Paid vacation, holidays, and parental leave
• Hybrid work flexibility
• Learning and certification reimbursement
• Access to advanced AI research and high-performance computing resources
• Career growth opportunities in AI, machine learning, and data science

Job Summary

We are seeking a highly skilled Cloud Security Engineer to join our cybersecurity team. In this role, you will design, implement, and maintain security controls across cloud platforms including AWS, Microsoft Azure, and Google Cloud Platform (GCP). You will work closely with DevOps, Infrastructure, and Security Operations teams to protect cloud environments, ensure regulatory compliance, and respond to security incidents. The ideal candidate has strong expertise in cloud architecture, identity and access management (IAM), network security, and automation.

Key Responsibilities

• Design, implement, and manage secure cloud infrastructure across AWS, Azure, and GCP.
• Develop and enforce cloud security policies, standards, and best practices.
• Configure and maintain Identity and Access Management (IAM), Multi-Factor Authentication (MFA), and Role-Based Access Control (RBAC).
• Implement Zero Trust security architecture and cloud-native security controls.
• Monitor cloud environments using SIEM, CSPM, and cloud security monitoring tools.
• Perform cloud vulnerability assessments, risk analyses, and security audits.
• Secure Kubernetes clusters, containers, and serverless applications.
• Automate cloud security tasks using Infrastructure as Code (Terraform, CloudFormation, ARM/Bicep).
• Configure Web Application Firewalls (WAF), firewalls, VPNs, and network segmentation.
• Collaborate with DevOps teams to integrate security into CI/CD pipelines (DevSecOps).
• Investigate and respond to cloud security incidents, threats, and vulnerabilities.
• Ensure compliance with industry standards such as ISO 27001, SOC 2, HIPAA, PCI-DSS, and NIST.
• Maintain cloud security documentation, policies, and incident reports.
• Stay up to date with emerging cloud threats, technologies, and security trends.

Required Qualifications

• Bachelor's degree in Cybersecurity, Information Technology, Computer Science, or a related field (or equivalent experience).
• 3–7+ years of experience in cloud security or cybersecurity.
• Hands-on experience with AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Strong understanding of cloud networking, IAM, encryption, and security architecture.
• Experience with SIEM, CSPM, and cloud monitoring solutions.
• Knowledge of Infrastructure as Code (Terraform, CloudFormation, ARM/Bicep).
• Experience securing Kubernetes, Docker, and containerized workloads.
• Familiarity with scripting languages such as Python, PowerShell, or Bash.
• Knowledge of security frameworks including NIST, CIS Benchmarks, ISO 27001, and SOC 2.
• Excellent analytical, troubleshooting, and communication skills.

Preferred Qualifications

• Cloud security certifications such as AWS Certified Security – Specialty, Microsoft Azure Security Engineer (AZ-500), or Google Professional Cloud Security Engineer.
• Experience with Microsoft Defender for Cloud, Prisma Cloud, Wiz, Orca Security, or Lacework.
• Knowledge of CI/CD security and DevSecOps practices.
• Experience with threat detection, incident response, and digital forensics.
• Familiarity with compliance frameworks including FedRAMP and PCI-DSS.

Technical Skills

• Cloud Platforms: AWS, Microsoft Azure, Google Cloud Platform (GCP)
• Identity & Access: IAM, Azure AD, Entra ID, MFA, RBAC
• Cloud Security: CSPM, CWPP, WAF, Zero Trust, Cloud Firewall
• Containers: Docker, Kubernetes, Amazon EKS, Azure AKS, Google GKE
• Infrastructure as Code: Terraform, CloudFormation, ARM, Bicep
• Programming: Python, PowerShell, Bash
• Monitoring & SIEM: Microsoft Sentinel, Splunk, Microsoft Defender for Cloud, AWS Security Hub, Azure Monitor
• DevSecOps: GitHub Actions, Jenkins, Azure DevOps, GitLab CI/CD
• Compliance: NIST, ISO 27001, SOC 2, HIPAA, PCI-DSS, CIS Benchmarks

Preferred Certifications

• AWS Certified Security – Specialty
• Microsoft Certified: Azure Security Engineer Associate (AZ-500)
• Google Professional Cloud Security Engineer
• Certified Information Systems Security Professional (CISSP)
• Certified Cloud Security Professional (CCSP)

Benefits

• Competitive salary with annual performance bonus
• Medical, dental, and vision insurance
• Paid time off and company holidays
• Flexible remote/hybrid work options
• Professional certification reimbursement
• Learning and development opportunities
• Career growth within a global cybersecurity team