Job Summary

We are seeking a talented AI Infrastructure Engineer to design, build, and optimize the cloud infrastructure that powers next-generation artificial intelligence and machine learning workloads. In this role, you will develop scalable GPU-based infrastructure, automate AI platform operations, and ensure high availability for large-scale model training and inference.

You will collaborate with AI researchers, Machine Learning Engineers, Platform Engineers, and DevOps teams to create secure, high-performance infrastructure supporting foundation models, Large Language Models (LLMs), computer vision, and generative AI applications.

Key Responsibilities

• Design, deploy, and maintain scalable AI infrastructure for machine learning and deep learning workloads.
• Build and optimize GPU clusters for AI model training and inference.
• Develop Infrastructure as Code (IaC) using tools such as Terraform and Ansible.
• Manage Kubernetes clusters and containerized AI workloads using Docker.
• Automate infrastructure provisioning, deployment, and monitoring.
• Optimize storage, networking, and compute resources for AI applications.
• Implement CI/CD pipelines for AI and machine learning platforms.
• Monitor infrastructure performance, availability, and resource utilization.
• Troubleshoot infrastructure, networking, and distributed computing issues.
• Collaborate with Machine Learning Engineers to support model deployment and lifecycle management.
• Implement security best practices, identity management, and access controls.
• Configure monitoring and logging using Prometheus, Grafana, and ELK Stack.
• Support distributed AI training frameworks and high-performance computing (HPC) environments.
• Ensure platform scalability, reliability, disaster recovery, and business continuity.
• Evaluate and adopt emerging cloud and AI infrastructure technologies.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related technical field.
• 4+ years of experience in cloud infrastructure, platform engineering, DevOps, or AI infrastructure.
• Strong experience with Kubernetes, Docker, and container orchestration.
• Experience with AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Knowledge of GPU computing, NVIDIA CUDA, and AI accelerator technologies.
• Experience with Infrastructure as Code (Terraform, CloudFormation, or Ansible).
• Strong Linux system administration and networking skills.
• Experience building CI/CD pipelines using GitHub Actions, Jenkins, or GitLab CI/CD.
• Familiarity with distributed computing and machine learning infrastructure.
• Strong scripting skills in Python, Bash, or Go.
• Excellent analytical, troubleshooting, and communication skills.

Preferred Qualifications

• Experience supporting Large Language Models (LLMs) and Generative AI workloads.
• Experience with distributed training frameworks such as PyTorch Distributed, Ray, or DeepSpeed.
• Knowledge of MLOps tools including MLflow, Kubeflow, and Airflow.
• Experience with NVIDIA DGX systems or GPU clusters.
• Familiarity with vector databases and Retrieval-Augmented Generation (RAG) architectures.
• AWS Certified Solutions Architect, Google Professional Cloud Architect, or Certified Kubernetes Administrator (CKA).
• Experience with high-performance computing (HPC) environments.

Technical Skills

Cloud Platforms

• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud Platform (GCP)

AI & Machine Learning Infrastructure

• GPU Computing
• NVIDIA CUDA
• NVIDIA DGX
• TensorRT
• Distributed Training
• MLOps
• Large Language Models (LLMs)
• Generative AI
• AI Model Deployment

Containerization & Orchestration

• Kubernetes
• Docker
• Helm
• OpenShift

Infrastructure as Code (IaC)

• Terraform
• Ansible
• CloudFormation

DevOps & CI/CD

• GitHub Actions
• GitLab CI/CD
• Jenkins
• Argo CD

Monitoring & Observability

• Prometheus
• Grafana
• ELK Stack (Elasticsearch, Logstash, Kibana)
• OpenTelemetry

Programming Languages

• Python
• Go
• Bash
• YAML

Databases & Storage

• PostgreSQL
• Redis
• MongoDB
• Amazon S3
• MinIO

Networking

• TCP/IP
• DNS
• VPN
• Load Balancing
• Network Security

Soft Skills

• Problem Solving
• Critical Thinking
• Team Collaboration
• Communication Skills
• Project Management
• Adaptability
• Time Management
• Innovation Mindset
• Leadership
• Continuous Learning

Benefits

• Competitive Base Salary
• Annual Performance Bonus
• Equity/Long-Term Incentive Eligibility
• Medical, Dental, and Vision Insurance
• Flexible Remote/Hybrid Work Options
• Paid Time Off (PTO)
• Paid Holidays
• Professional Certification Reimbursement
• Learning and Development Programs
• Wellness Programs
• Employee Assistance Program (EAP)
• Parental Leave
• Life and Disability Insurance