engineering
Posted Mar 12AI Engineering Manager, Product Engineering - US Remote
at TRM Labs
United StatesRemote
Responsibilities
- BUILD A SAFER WORLD.
- - Own execution of key AI‑powered product initiatives end‑to‑end, from shaping problem statements and 0→1 prototypes to launch, iteration, and scale.
- - Drive predictable delivery while maintaining high standards for quality, reliability, and maintainability in a fast‑moving environment.
Requirements
- TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime.
- As an Engineering Manager on the AI Product Engineering team, you will re-imagine from first principles how people interact with software — unencumbered by the legacy of traditional SaaS.
- You'll lead a multidisciplinary pod of frontend, backend, and full-stack engineers to build tooling that enables crime fighters to keep pace with the growing threat of AI-powered crime.
- You'll partner closely with Product, Design, and AI-focused teams to translate ambiguous ideas into intuitive, scalable product experiences.
- You review code, jump into PRs when needed, and stay close to the architecture. - You’re obsessed with building at the frontier of AI — experimenting with LLMs, agents, and tools like Claude Code, and comfortable orchestrating multiple agents in parallel. - You don’t need heavy PM structure.
- - Partner closely with Product and Design on roadmap planning, tradeoffs, and prioritization, especially where AI can unlock step‑function improvements in user workflows.
- - Collaborate cross‑functionally with other engineering teams (data, platform, AI/agents) to integrate advanced capabilities into clear, explainable user experiences.
- - Establish strong engineering fundamentals — clear ownership, documentation, observability, testing, and operational rigor — for AI‑infused product surfaces.
- Experience building or integrating AI/LLM-powered features into production systems.
- You understand the practical realities of shipping AI — iteration, evaluation, reliability, and UX tradeoffs. - Proven ability to operate in ambiguous problem spaces, move quickly without heavy process, and turn early ideas into shipped product. - Technical depth to review code, guide architecture, and make sound tradeoffs across frontend, backend, and AI-integrated systems. -