Sholinganallur, Tamil Nadu

Job Summary

Role Summary

Key Responsibilities

Key Responsibilities
- Embed Responsible AI principles such as fairness, accountability, transparency, safety, and privacy into AI and GenAI solution designs.
- Implement technical controls for bias detection, bias mitigation, explainability, and model governance.
- Design and enforce guardrails for LLM systems including input validation, output moderation, and policy enforcement.
- Conduct AI risk assessments prior to production deployment.
- Ensure compliance with enterprise AI policies, regulatory requirements, and industry standards.
- Implement monitoring mechanisms for hallucinations, harmful outputs, data leakage, and misuse.
- Continuously monitor AI systems for bias, drift, fairness, and ethical risk post-deployment.
- Support audits, architecture reviews, and governance boards.
- Advise engineering and product teams on responsible AI best practices.

Skill Requirements

Required Skills & Experience
- Solid understanding of AI, ML, and Generative AI systems including LLMs.




- Experience with responsible AI concepts such as fairness, explainability, transparency, and accountability.
- Familiarity with AI governance, risk, and compliance frameworks.
- Programming experience in Python is preferred.
- Experience working with AI monitoring, logging, and audit mechanisms.
- Ability to collaborate with legal, security, compliance, and engineering teams.

Other Requirements

Experience Level
- 14+ years of overall experience in software, data, or AI engineering.
- 2-4+ years of experience in AI risk, governance, security, ethics, or compliance-focused roles.
- Hands-on exposure to GenAI or LLM systems in production environments is highly desirable.

Success Measures
- AI systems deployed with embedded responsible AI controls and governance.
- Reduced ethical, regulatory, and reputational risk from AI deployments.
- Increased enterprise and client trust in AI-driven solutions.
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