Program Management - AI Governance

Rocket Companies · Chennai

Source and collection record

Last observed by our collector: 9 October 2026 at 12:02 am IST. This is not a manual review or a confirmation from the employer.

Employer requisition: R-084929

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Collected role description

If you thrive at the intersection of technology, risk, and cross-functional leadership, this is your launchpad. Own the end-to-end program plan for AI governance initiatives, including milestones, dependencies, risk tracking, and executive-level status reporting. Serve as the central coordination hub across legal, security, engineering, data science, procurement, and compliance teams working on AI risk management, model evaluation, and policy implementation. Track and drive progress against governance frameworks such as the NIST AI Risk Management Framework (AI RMF), mapping deliverables to its core functions — Govern, Map, Measure, and Manage. Maintain a working knowledge of major LLM providers and platforms (e.g., Anthropic/Claude, OpenAI, and others) to understand technical constraints, model behavior, and vendor-specific governance or safety documentation. Facilitate governance oversight processes including review boards, risk assessments, and sign-offs — ensuring every decision is documented, traceable, and defensible. Identify gaps, blockers, and cross-team risks early and relentlessly drive resolution before they become roadblocks. Translate complex technical and regulatory concepts into clear, actionable updates for both engineering teams and executive stakeholders. Support the development of internal policies, documentation, and audit-readiness materials related to responsible AI use across the organization. Proven program or project management experience, ideally in a regulated, technical, or compliance-driven environment. Working familiarity with AI governance concepts and frameworks (e.g., NIST AI RMF or similar risk and compliance models) — deep technical AI expertise is not required, but a genuine comfort with learning and discussing LLM concepts is essential. General awareness of the current AI vendor landscape (Anthropic, OpenAI, etc.) Strong stakeholder management skills with a demonstrated ability to align diverse teams — both technical and non-technical — around shared timelines and goals. Excellent organizational, communication, and documentation skills that bring clarity to complexity. Experience with AI/ML product development lifecycles and the unique governance challenges they present. Background in risk management, compliance, legal, or audit functions. Familiarity with model cards, system cards, or AI safety documentation and how they support transparency and accountability in AI deployment. About Us.