Compliant-Ready AI for the Enterprise. Backed by Y Combinator.
About the role
Every AI application needs policies that define acceptable behavior, and guardrails built and tuned against those policies. Legal, risk and compliance teams hold much of the knowledge those policies depend on. They have no prior experience or mandate to write policy definitions for guardrails or to annotate data, and there is usually no process that brings them into guardrail creation and optimization. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 2 to 4 years of product management experience in GRC, regtech, legal tech, risk management or enterprise workflow software
- Experience working directly with legal, risk, compliance or audit teams at large enterprises, and an understanding of their mandates, incentives and how they make and document decisions
- A track record of bringing a team into a new process or responsibility it did not previously own, in an organization where that team did not report to you or to the project sponsor
- Understanding of enterprise decision-making: how budget holders, reviewers and approvers differ, and how to secure time and sign-off from teams outside the buying organization
- Working knowledge of how regulated enterprises govern models and AI, including model risk management practices such as SR 11-7 and frameworks such as the EU AI Act, NIST AI RMF and ISO/IEC 42001
- Enough technical understanding of LLMs, evaluations and guardrails to discuss precision, recall and false positive tradeoffs with engineers and explain them to non-technical reviewers
More about this role
Dynamo AI builds the platform enterprises use to bring AI applications to production and keep them there. Our products cover risk assessment, evaluation, runtime guardrails and observability for generative AI and agentic systems. We work with enterprises in regulated industries, including financial services, insurance, healthcare and defense.
Every AI application needs policies that define acceptable behavior, and guardrails built and tuned against those policies. Legal, risk and compliance teams hold much of the knowledge those policies depend on. They have no prior experience or mandate to write policy definitions for guardrails or to annotate data, and there is usually no process that brings them into guardrail creation and optimization. They are also rarely the teams that buy our products, which are usually purchased by security and AI platform leaders.
As Product Manager for AI Governance & Compliance, you will design how these teams take part in policy writing, guardrail creation and guardrail optimization where no such process exists today. That means working out who needs to contribute, what they sign off on, and how their participation is secured through the economic...
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