Forward Deployed Engineer - US National Security

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 a Forward Deployed Engineer, you will work directly with TRM's national‑security customers — deploying our platform into their environments, sitting with the people who use it, and building what the mission actually needs.

This is a generalist engineering role. In a given quarter you might ship application code, debug a Kubernetes workload in a restricted environment, design a data schema, stand up cloud infrastructure, or prototype an entirely new capability because a customer described a problem nobody has solved yet. You will often be the only TRM engineer in the room. What you build enables our government customers to use TRM securely in the most demanding environments in the world — and carries what you learn there back into the product.

• Deploy, integrate and operate TRM's platform inside customer environments - cloud and air-gapped - and own the outcome, not just your slice of it.
• Sit directly with mission users, translate what they need into working software, and build it: integrations, data pipelines, and prototypes that prove out a capability before it's a product.
• Deliver across whatever the problem requires — application code, Kubernetes, cloud infrastructure, databases, data flow - rather than staying inside one specialty.
• Act as the technical bridge back to TRM's product and engineering teams, carrying mission context into the roadmap.
• Diagnose and resolve hard problems in constrained environments, with limited tooling and limited outside help.

• Strong programming ability in Python and/or Node.js/Type Script, with real fluency developing with AI — coding agents and LLM tooling are part of how you ship, and you have judgment about where they help and where they don't.
• Hands‑on Kubernetes: deploying, debugging and reasoning about real workloads. Maintaining someone else's cluster is not the same thing.
• Production AWS experience — building environments, not just consuming them.
• Working fluency with relational databases (PostgreSQL or similar): schema design, query tuning, moving data around safely.
• Range. Concrete examples of delivering outside your primary specialty — a new language, datastore or platform you picked up because the project needed it.
• Outstanding written and verbal communication. You will be the only engineer in front of a customer regularly, and comfort there is not optional.

• Infrastructure as code (Terraform) and Git Ops (Argo CD)
• Data engineering at scale — orchestration, streaming, columnar/analytics stores
• Distributed systems design and debugging
• Building machine learning or agentic systems
• Deep Linux/Unix and networking, especially in restricted or disconnected environments
• Prior delivery inside classified or otherwise regulated government environments

• Small, senior and high-trust. Everyone owns a real surface end to end; nobody is handed a queue of tickets.
• We are the closest team at TRM to our customers, and we put them first. We do what it takes for their mission to succeed.
• We align to US-eastern hours, on‑site and remote, and we communicate across a lot of channels — high-side chat, high-side and low-side email, Slack, phone, Signal, Google Meet — switching between them fast when the situation calls for it.
• Weekly team syncs plus project check‑ins. We keep tracking current in Linear…