Note: The job is a remote job and is open to candidates in USA. 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 lead a multidisciplinary team to develop innovative tools that enhance crime fighting capabilities and improve user workflows.
Responsibilities
- Lead and develop a pod of engineers across frontend, backend, and full‑stack disciplines, setting a high bar for craftsmanship, pace, and ownership
- Own execution of key AI‑powered product initiatives end‑to‑end, from shaping problem statements and 0→1 prototypes to launch, iteration, and scale
- Partner closely with Product and Design on roadmap planning, tradeoffs, and prioritization, especially where AI can unlock step‑function improvements in user workflows
- Drive predictable delivery while maintaining high standards for quality, reliability, and maintainability in a fast‑moving environment
- Provide technical leadership through design reviews, architectural discussions, and unblocking engineers across the stack (FE + BE + integrations)
- 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
- Foster a culture of high trust, high velocity, and candid communication, where hiring and developing exceptional talent is treated as a first‑class responsibility
Skills
- 5+ years of software engineering experience and 2–5+ years of people management experience, leading multidisciplinary product teams that ship user-facing software
- Strong product engineering background building workflow-heavy or data-rich applications end-to-end, from 0→1 through scale
- 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
- Experience partnering closely with Product and Design in fast-moving environments, balancing speed, quality, and user experience
- Strong communication skills and comfort engaging directly with customers to inform product direction
- Experience scaling or evolving product engineering pods
- Background in B2B or enterprise software
- Experience with data-rich, workflow-heavy, or real-time products
- Familiarity with event-driven systems or complex integrations
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