Technical Program Manager, AI Model Assurance

About the Team

JV AI & Systems Integrity is the independent function inside the TikTok USDS Joint Venture security organization that opines on whether generative AI features shipping to US users meet the JV's safety and content commitments. We operate the approval gates, testing programs, deviation adjudication, and audit-facing evidence pipeline for every JV-covered GenAI surface — including CapCut, Gauth, TikTok GenAI features, and emerging apps like Pippit, Dreamina, and Hypic. We work in close partnership with legal, safety, and engineering teams.

About the Role

The Technical Product Manager for AI Model Assurance owns the roadmap for how our Content Assurance program is instrumented and run in the model assurance area. Where our Assurance Analysts drive day-to-day approvals, dossiers, and oversight reports, and our engineering team builds and operates the underlying platform, you are the person who decides what to build next, how success is measured, and how the pieces fit together into a coherent, audit-ready system.

This is a technical product role, not a coordination role. You will write the requirements and success metrics that engineering builds against, and you will be accountable for whether our approval workflow gets faster, more consistent, and more defensible each quarter.

Responsibilities

• Own the Model Assurance product roadmap end-to-end: intake, approval workflow, change detection, evaluation dossier tooling, dashboards, and audit evidence pipeline. Sequence work against program risk, launch volume, and audit milestones.
• Translate CA policy, control catalog, and analyst pain points into crisp requirements, success metrics, and acceptance criteria that engineering can build against without ambiguity.
• Partner with the engineering team on design, trade-off calls, and delivery; drive prioritization when scope and time do not both fit.
• Define the metrics that describe program health — approval throughput and SLA, materiality mix, unnotified-change incidents, envelope breaches, validation coverage, evidence readiness — and make sure the systems of record can produce them without hand-updated trackers.
• Sit inside the launch review loop for high-signal releases; use those cases to sharpen requirements for the next generation of tooling instead of only closing the current ticket.
• Work directly with the Assurance Analysts to identify the highest-cost manual steps in the workflow, size the opportunity, and turn them into prioritized roadmap items with clear before/after targets.
• Partner with GRC on audit and third-party pre-assessment needs so evidence capture, versioning, and retrieval are a product capability, not a fire drill.
• Write and maintain the PRDs, design reviews, and change logs that make the program reproducible and audit-defensible.
• Report to CA leadership on roadmap progress, program KPIs, and the next set of investments, and represent Model Assurance in cross-functional forums.

Minimum Qualifications

• Bachelor's degree in a technical, risk, or policy-adjacent field (e.g., Computer Science, Information Security, Data / Analytics, Trust & Safety, Compliance), or equivalent practical experience.
• 5+ years of technical product management, model-risk / model-ops product work, or platform / internal-tools product ownership, including at least one role owning a roadmap for a cross-functional workflow with hard SLAs or audit exposure.
• Demonstrated ability to write PRDs, requirements, and success metrics that engineering teams can build against — not high-level narratives that hand implementation choices back to engineering.
• Direct working knowledge of at least one of: generative AI / LLM systems, content moderation classifiers, trust & safety operations, model-risk management, or AI/ML evaluation. You should be able to reason about an evaluation dossier and challenge conclusions on substance.
• Fluency reading SQL and interpreting dashboards well enough to define metrics precisely, validate what the numbers actually mean, and push back when a proposed metric doesn't answer the question.
• Demonstrated ability to drive engineering and cross-functional partners (policy, legal, security, GRC) to a decision on a fixed clock.
• Written communication strong enough to author PRDs, design reviews, and leadership updates without heavy editing.

Preferred Qualifications

• Prior work under the USDS National Security Agreement, a bank / model-risk governance regime (e.g., SR 11-7), or a formal AI management system (NIST AI RMF, ISO/IEC 42001).
• Experience owning product for a third-party pre-assessment or independent audit workstream — evidence capture, control walk-through packs, and finding-remediation tracking.
• Familiarity with evaluation harnesses, red-teaming pipelines, or adversarial test set management for text, image, audio, or video GenAI systems.
• Experience defining metrics from raw event data and working with BI / dashboarding tools (e.g., Tableau, Looker, internal equivalents).