Principal Product Manager, AI Build Governance

The Challenge

AI Governance is one of the fastest-emerging categories in enterprise software. The first Gartner® Magic Quadrant™ for AI Governance Platforms was published this year, and OneTrust is named a Visionary in it.

OneTrust is looking for a Principal Product Manager to own the developer-facing products in our AI Governance solution to own it’s early success and growing adoption.

These products live within the AI development lifecycle an engineer already follows when it builds an AI system: writing prompts, wiring up retrieval and tools, evaluating what the system actually does, and deciding it is ready to ship. You own the governance tooling and checks that live at those steps, and the work is to turn governance requirements into controls a developer can implement and test.

You will define what we build, ship it with a dedicated engineering and design team, and prove it with measurable outcomes. You will work daily with Engineering, UX, and other Product Managers, and you will prototype and build with modern AI development tools.

Your Mission

Define and own the product strategy, roadmap, and packaging for OneTrust's developer-facing AI governance products

Translate governance requirements into technical requirements, tests, and controls that developers can act on

Own the developer experience end to end, including SDK design, APIs, documentation, samples, and CI/CD integration

Set requirements earlier in the lifecycle carry into the build, and that signals from production carry back into future evaluations

Work with design partners and early access customers to validate direction against real engineering teams

Partner with Product Marketing, Sales Engineering, on positioning, launches, and the technical narrative

Own the outcomes: developer adoption, integration depth, and the revenue and retention these products influence

You Are

A hands-on product leader with a track record of strong product ownership and demonstrated product-led growth. You have shipped developer-facing products, and you are comfortable with ambiguity. You work well at speed, building for where the market is right now and revising as it moves.

Builder — You prototype. When a team is deciding on an API shape or an interaction, you open the tools and show them one. You are comfortable in a repo and an SDK.

Developer empathy — You have built products where the user was an engineer, and you know adoption is won on time-to-first-integration, documentation, and good defaults.

Collaborator — Most of what you own depends on work other teams are doing, and you spend as much time inside their plans as your own. You build alignment and confidence across other teams without having authority over them.

Zero-to-one — You have taken new products from nothing to real customers and real revenue, knowing full well what it takes.

Your Experience Includes

Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience

12+ years of product management experience in enterprise software, including end-to-end ownership of a technical product area

Demonstrated success taking new products from concept to shipped, adopted, and generating revenue

Strong working knowledge of the modern AI stack: LLMs and model providers, agents and tool calling, RAG pipelines, prompts, and their failure modes

Familiarity with AI evaluation practice, including benchmarking, offline and online evaluation, red teaming, and safety testing

Proven ability to partner deeply with Engineering, UX, Security, and Legal, and to earn technical credibility with senior engineers

Exceptional communication skills with the ability to articulate vision, create alignment, and represent new products credibly

A major plus:

Experience building developer tools or developer platforms — SDKs, APIs, CLIs, IDE extensions, CI/CD integrations, or testing frameworks — where engineers were your primary user

Fluency using AI tools to build product: prototyping in code with coding agents, building your own evals, and shipping AI-assisted workflows

Also preferred:

Hands-on experience with AI security or safety controls such as guardrails, prompt injection defenses, content filtering, or output validation

Familiarity with AI regulations and frameworks such as the EU AI Act, NIST AI RMF, and ISO 42001

Experience with design partner programs, early access programs, or developer relations