TRM Labs
Forward Deployed Engineer - US National Security
About this role
TRM Labs seeks a Forward Deployed Engineer to embed with US national security customers, deploying and integrating our AI-powered investigation platform into their environments. You'll own end-to-end technical delivery across application code, infrastructure, and data systems—acting as the sole engineer on-site and translating mission needs into working software.
What you'll do
- Deploy and operate TRM platform in customer environments (cloud and air-gapped), owning full outcomes
- Translate customer mission requirements into software solutions: integrations, data pipelines, and prototypes
- Develop across Python/Node.js, Kubernetes, AWS, and databases as needed by the problem
- Debug and resolve complex technical issues in constrained environments with limited tooling
- Serve as technical bridge between customer needs and TRM's product and engineering teams
- Maintain rapid incident response and knowledge documentation for stakeholders
What they're looking for
- Python and/or Node.js/TypeScript programming with AI/LLM experience
- Hands-on Kubernetes deployment and debugging in production
- AWS infrastructure design and environment building
- PostgreSQL and relational database schema design, query tuning
- Strong written and verbal communication for customer-facing work
- Ability to rapidly learn new technologies and platforms as projects demand
- Linux/Unix systems and networking in restricted environments (bonus)
- Infrastructure as code (Terraform) and GitOps practices (bonus)
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TRM Labs
TRM Labs builds AI-powered intelligence products designed to detect and disrupt financial crime through advanced machine learning and investigative tools. The company is hiring backend engineers, ML infrastructure engineers, AI research engineers, and AI agent engineers to develop scalable platform infrastructure, GPU-backed systems, model optimization capabilities, and LLM-based agentic applications.
- Website
- trmlabs.com
Likely interview questions
- Describe a time you shipped code in a language or technology you weren't primary in—what triggered the need and how did you approach learning it?
- Walk us through how you've debugged a Kubernetes issue in production; what was broken, how did you diagnose it, and what did you change?