AI Ethics And Responsible AI Specialist

Job Description

We are seeking an experienced AI Ethics & Responsible AI Specialist to help ensure that our artificial intelligence and machine learning solutions are developed, deployed, and governed responsibly. This role is responsible for establishing ethical AI practices, assessing AI risks, and implementing governance frameworks that promote fairness, transparency, accountability, privacy, and regulatory compliance across AI initiatives.

The ideal candidate will work closely with AI Engineers, Data Scientists, Product Managers, Legal, Security, Privacy, and Compliance teams to evaluate AI systems throughout their lifecycle. You will help identify and mitigate algorithmic bias, improve model explainability, develop AI governance policies, and ensure compliance with emerging AI regulations and industry standards.

This position requires a strong understanding of machine learning, AI governance, risk management, data privacy, and ethical AI principles, along with the ability to communicate complex technical and regulatory concepts to both technical and business stakeholders.

Key Responsibilities

• Develop and maintain Responsible AI governance frameworks, policies, and standards.
• Conduct AI risk assessments throughout the AI and machine learning lifecycle.
• Evaluate AI models for fairness, bias, transparency, robustness, explainability, and accountability.
• Collaborate with AI Engineering and Data Science teams to implement ethical AI best practices.
• Perform algorithmic bias testing and recommend mitigation strategies.
• Ensure compliance with AI regulations, privacy laws, and industry standards.
• Develop AI model documentation, model cards, and governance reports.
• Support AI audits, regulatory assessments, and internal compliance reviews.
• Establish AI monitoring processes for model performance, drift, fairness, and compliance.
• Work with Legal, Privacy, Security, and Risk teams to evaluate AI-related risks.
• Define AI governance controls for Generative AI, Large Language Models (LLMs), and AI-powered products.
• Promote responsible data collection, usage, and retention practices.
• Deliver Responsible AI awareness sessions and training programs for technical and business teams.
• Research emerging AI regulations, governance frameworks, and ethical AI trends.
• Recommend continuous improvements to strengthen organizational AI governance and compliance.

Required Qualifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, Cybersecurity, Ethics, Public Policy, Law, or a related field.
• 3–6+ years of experience in AI governance, Responsible AI, machine learning, data science, risk management, cybersecurity, compliance, or technology governance.
• Strong understanding of machine learning concepts and AI development lifecycle.
• Experience with AI governance frameworks, AI risk management, or model governance.
• Knowledge of AI fairness, explainability, model validation, and algorithmic bias mitigation techniques.
• Familiarity with AI regulations, data privacy requirements, and enterprise compliance programs.
• Excellent communication, analytical, documentation, and stakeholder management skills.
• Experience working with cross-functional teams in enterprise environments.

Preferred Qualifications

• Master’s degree in Artificial Intelligence, Data Science, Computer Science, Public Policy, Ethics, or a related field.
• Experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
• Experience supporting AI governance for cloud-based AI platforms.
• Familiarity with AI model lifecycle management and MLOps.
• Knowledge of enterprise risk management and cybersecurity governance.
• Experience participating in AI ethics committees or governance boards.

Preferred Technical Skills

• Python
• SQL
• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• LangChain
• Hugging Face Transformers
• TensorFlow
• PyTorch
• Scikit-learn
• MLflow
• AI Governance
• Responsible AI
• Model Risk Management
• AI Fairness & Bias Detection
• Explainable AI (XAI)
• AI Model Validation
• Data Privacy
• Risk Assessment
• Governance, Risk & Compliance (GRC)
• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)
• Git
• Docker
• Kubernetes

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning – Specialty
• Certified Information Systems Security Professional (CISSP)
• Certified Information Security Manager (CISM)
• ISO/IEC 42001 AI Management Systems (awareness or lead implementer)
• NIST AI Risk Management Framework (AI RMF) knowledge
• Certified Data Privacy Solutions Engineer (CDPSE)