Lead Responsible AI Engineer
Core
Lead the design, implementation, and operationalization of responsible AI, safety, quality, evaluation, and governance practices across GenAI and agentic AI solutions to ensure systems are safe, reliable, and fit for enterprise use.
Role type
Senior IC Lead Responsible AI Engineer (GenAI/Agentic AI)
Builds
GenAI and agentic AI products with embedded safety controls, validation strategies, and governance frameworks
Domain
Enterprise AI, Generative AI, Agentic Workflows, AI Governance
Deliverable
production ML models | product features
Required skills
LLM system architecture, RAG pipeline design, agentic workflow orchestration, AI validation strategy, red-teaming and adversarial testing, fairness and bias evaluation, AI observability and tracing, CI/CD quality controls, enterprise risk management, NIST AI RMF implementation
Preferred skills
Model Context Protocol (MCP) patterns, multi-agent coordination, vector search quality assessment, reusable safety control frameworks, token usage analytics, human-in-the-loop escalation models
Technologies
LangSmith, TruLens, DeepEval, Guardrails AI, NeMo Guardrails, Azure AI Content Safety, Azure Monitor, Application Insights, OpenTelemetry, MLflow, Vertex AI monitoring, watsonx.governance, Azure DevOps, GitHub, pytest, Python
Responsibilities
Define and operationalize AI validation strategies covering functional correctness, hallucination risk, and retrieval quality; Design and implement evaluation frameworks for relevance, safety, groundedness, and business outcome alignment; Embed guardrails, prompt controls, and safety-oriented design patterns into solution architectures; Drive adoption of governance and auditability practices including automated test scripts and traceability; Mentor engineers on AI testing, safety validation, and production monitoring approaches; Contribute reusable assets such as test harnesses, prompt evaluation templates, and red-team patterns
Seniority
Senior, hands-on IC with leadership responsibilities
