Forward Deployed Engineer - US National Security at TRM Labs

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. The impact you will have: 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. What we’re looking for: Strong programming ability in Python and/or Node.js/TypeScript, 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. Bonus, not required — depth in any of these raises the bar Infrastructure as code (Terraform) and GitOps (Argo CD) Data engineering at scale — orchestration, streaming, columnar/analytics stores Distributed systems design and debug