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Manager of Risk & Governance (AI Safety)

Reflection AI

Job at a glance

Category
AI Governance
Work arrangement
On-site
Location
San Francisco, CA
Posted
Jul 27, 2026
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Reflection AI is hiring a Manager of Risk & Governance (AI Safety) in San Francisco, CA. This is a AI Governance job in the governance, risk, and compliance field. Review the full details below and apply directly with Reflection AI.

Our Mission Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all. Role Overview The Head of Risk & Trust Governance is responsible for designing, operating, and continuously maturing the organization's enterprise risk management and control environment. This leader owns the full lifecycle of risk governance, from obligation identification and control architecture to risk measurement, reporting, and external representation, ensuring the organization operates within its stated risk appetite while advancing its strategic objectives. Sitting at the intersection of risk, compliance, technology, and AI safety, this role is uniquely positioned to shape how the organization understands and responds to a dynamic regulatory and operational risk landscape. The ideal candidate brings deep expertise in enterprise risk frameworks, a systems-level perspective on controls design, and the executive presence to represent the organization's risk posture to regulators, customers, and other critical external stakeholders. This is a high-visibility, high-impact role that operates across all business functions. Success requires the ability to translate complex risk concepts into actionable governance structures, influence without direct authority, and build trusted relationships internally and externally. What You'll Do Control Environment & Risk Framework Architecture Architect and govern a control environment that drives efficient, prioritized adherence to organizational obligations in alignment with management's objectives and stated risk appetite. Design and continuously operate an enterprise risk management framework spanning risk identification, measurement, mitigation, monitoring, and reporting, contextualized against the organization's obligations, objectives, and risk tolerance. Establish a disciplined approach to risk prioritization that balances operational efficiency with the rigor required to address high-severity exposures across the enterprise. Policy, Standards & Controls Governance Architect and govern the organization's policy and standards issuance lifecycle, ensuring timely coverage of emerging obligations and strategic priorities. Oversee the design, implementation, and ongoing operation of controls and guardrails that drive adherence to

Full responsibilities and requirements are on Reflection AI's application page.

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About Reflection AI
Hiring for governance, risk, and compliance jobs on GRC Careers.
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Location and market context

This job is based in San Francisco, CA on-site. Local candidates benefit from being close to Reflection AI's teams and regional hiring market. Confirm the exact in-office expectation and any relocation support with the employer.

About AI governance jobs

AI governance sits at the intersection of policy, risk, and engineering. Teams are standing up model inventories, use-case intake and review, risk classification, and control monitoring as regulation and board scrutiny of AI intensify. Jobs like this one are typically evaluated against frameworks such as NIST AI RMF, ISO/IEC 42001, the EU AI Act, and internal model-risk and privacy practices.

How to position yourself for this AI governance job

Strong candidates emphasize experience translating policy into operational controls, working across legal, compliance, security, product, and data teams, documenting AI system risks, and supporting governance processes. In your resume and outreach, tie your experience to how Reflection AI would apply NIST AI RMF, ISO/IEC 42001, the EU AI Act, and internal model-risk and privacy practices, and lead with concrete outcomes rather than duties.

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