Responsible AI Engineer

Responsibilities

• Develop and implement fairness, bias detection, and transparency frameworks for AI systems.
• Define policies and guardrails for safe LLM interactions, multi-agent orchestration, and decision-making systems.
• Design pipelines to monitor AI reliability, safety, and hallucination rates.
• Build metrics to track bias, fairness, interpretability, and ethical compliance.
• Ensure compliance with GDPR, SOC2, HIPAA, ISO 27001, and other AI governance standards.
• Implement XAI (Explainable AI) techniques to make models and agent decisions interpretable.
• Collaborate with AI Engineers, AgentOps, and Data Architects to integrate responsible AI practices across the stack.

Requirements

• 3–6 years of experience in AI/ML engineering, AI governance, or AI safety research.
• Strong knowledge of AI fairness, interpretability, and Responsible AI frameworks.
• Hands-on experience with evaluation tools such as OpenAI Evals, Ragas, or DeepEval.
• Proficiency in Python and data analysis frameworks.
• Deep understanding of LLM architectures, RAG pipelines, and multi-agent workflows.
• Familiarity with compliance and governance standards like GDPR, SOC2, or ISO.

Preferred Qualifications

• Exposure to reinforcement learning (RLHF, RLAIF, reward modeling).
• Experience with Responsible AI monitoring in regulated industries such as BFSI or Healthcare.
• Knowledge of observability platforms like Weights & Biases, Arize AI, or Prometheus.
• Contributions to Responsible AI open-source projects or academic research.

About the Company

XenonStack is a fast-growing Data and AI Foundry for Agentic Systems. We enable enterprises to gain real-time and intelligent business insights through innovative platforms for AI agents, vision AI, and inference infrastructure. Our mission is to accelerate the transition to AI + Human Intelligence by building systems that are powerful, safe, transparent, and accountable.