Job Opportunities API

The Public Ledger of Openings

← Back to the ledger

AI Engineering Manager, Product Engineering - US Remote

Trm Labs
CompanyTrm Labs
CategoryEngineering
LocationUnited States
RemoteRemote
EmploymentNot stated
LevelManager
SalaryNot stated by the employer
Posted12 Mar 2026
Last verified5 Aug 2026
SourceEmployer ATS (ashby)
Applications are handled by the employer, not by us.Apply on the employer's site →
Description
BUILD A SAFER WORLD. TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. TRM's platforms enable investigators to trace illicit activity, build cases, and construct operating pictures of threat networks. Leading agencies and businesses worldwide rely on TRM to make the world safer and more secure. 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. That means shipping workflows that are more autonomous, auditable, and 10x more effective than current SaaS-based tools. This role blends people leadership, technical judgment, and end-to-end ownership — from 0→1 product bets through to scaled, reliable production systems. You'll partner closely with Product, Design, and AI-focused teams to translate ambiguous ideas into intuitive, scalable product experiences. This role is for you if… - You’re an Engineering Manager who still ships. 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. You turn ambiguity into momentum and move fast without waiting for perfect specs. - You love talking to customers and use those conversations to shape what gets built. - You hire and inspire exceptional engineers — and treat team quality as a product decision. - You want real ownership: 0→1 bets, scaled systems, and the culture that makes both possible. The impact you’ll have here: - 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. What we’re looking for: - 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 ac