EY - GDS Consulting - AI and DATA - Responsible AI - Senior

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Responsible AI Engineer (Governance & Safety) - Senior

Role summary

You will lead AI governance, safety, and compliance engineering—operationalizing LLMOps/Agentic Ops, security and privacy controls, LLM evaluation, and guardrails/ethics for production AI systems. The remit spans policy to code: frameworks, controls, tooling, documentation, red teaming, and continuous evaluation.

Key responsibilities

• Establish and run LLMOps/Agentic Ops practices (lifecycle, approvals, versioning, observability, incident response/playbooks) integrated with platform tooling.
• Define and enforce governance & security controls (PII protection, data residency, model access, content safety, jailbreak/prompt injection defenses), integrating with enterprise security.
• Build LLM evaluation pipelines (groundedness/faithfulness, toxicity/PII, bias/fairness, robustness) and quality gates for pre prod and ongoing post deployment monitoring.
• Implement guardrails/ethics (policy as code, allow/deny lists, safety filters, red teaming harnesses) and ensure compliant documentation (model cards, data sheets, DPIAs).
• Contribute production grade Python libraries, policies, and APIs that product teams can adopt “as a service”; partner with platform teams on AWS/Azure controls.

Must have skills

• LLMOps/Agentic Ops patterns and tooling
• Governance/Security (threat modeling for LLMs, privacy, access controls)
• LLM Evaluation frameworks (human+automatic metrics; eval harnesses)
• Guardrails/Ethics techniques and incident playbooks
• Python
• AWS/Azure
• API development for governance services

Good to have

• Familiarity with RAG/advanced agentic AI to guide safe design choices

Qualifications & experience

• B.Tech/M.Tech/MS in CS/EE or equivalent.
• 4+ years in Responsible AI Engineering

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