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AI Engineering Manager, Product Engineering

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TRM Labs

Blockchain intelligence company providing tools to detect, investigate, and manage crypto-related fraud, financial crime, and compliance for institutions and government agencies.

450 Townsend Street, San Francisco, CA 94107, United States
About TRM Labs

TRM Labs provides blockchain intelligence for investigations and compliance, offering products such as forensics, wallet screening, entity screening, transaction monitoring, and APIs. It serves financial institutions, crypto businesses, and public sector agencies to trace funds, assess risk, and build cases across digital assets.

View jobs by TRM Labs

Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will lead a multidisciplinary pod of frontend, backend, and full‑stack engineers to design, build, and ship AI‑infused product surfaces. You will review code, drive architecture decisions, prototype AI/LLM features, and own execution from 0→1 through scale. You will partner with Product and Design, engage with customers to inform product direction, and establish engineering fundamentals such as observability, testing, documentation, and reliable operations.

Requirements

  • 5+ years of software engineering experience
  • 2–5+ years of people management experience leading multidisciplinary product teams
  • Proven product engineering experience building workflow‑heavy or data‑rich applications end‑to‑end
  • Experience building or integrating AI/LLM‑powered features into production systems
  • Ability to operate in ambiguous problem spaces and turn early ideas into shipped product
  • Technical depth to review code, guide architecture, and make tradeoffs across frontend, backend, and AI systems
  • Experience partnering closely with Product and Design
  • Strong communication skills and comfort engaging directly with customers

Responsibilities

  • Lead and develop a pod of engineers across frontend, backend, and full‑stack disciplines
  • Own execution of AI‑powered product initiatives end‑to‑end
  • Partner with Product and Design on roadmap planning and prioritization
  • Drive predictable delivery while maintaining quality, reliability, and maintainability
  • Provide technical leadership through design reviews and architectural guidance
  • Review code and unblock engineers across the stack
  • Collaborate cross‑functionally to integrate advanced AI capabilities into user experiences
  • Establish engineering fundamentals including ownership, documentation, observability, and testing
  • Hire and develop exceptional engineering talent