Agent Engineer - US Remote

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Agent Engineer - US Remote United States | Remote 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. The AI Engineering Team is chartered with enabling next-generation AI applications, with a special focus on Large Language Models (LLMs) and agentic systems. Our mission is to build robust pipelines, high-performance infrastructure, and operational tooling that allow AI systems to be deployed with speed, safety, and scale. We manage petabyte-scale pipelines, serve models with millisecond-level latency, and provide the observability and governance needed to make AI production-ready. We're also deeply involved in evaluating and integrating cutting-edge tools in the LLM and agent space - including open-source stacks, vector databases, evaluation frameworks, and orchestration tools that unlock TRM's ability to innovate faster than the market. The impact you will have: - Architect and implement a robust agentic framework that supports tool use, context retrieval, memory, and planning - Build intelligent, modular agents that automate investigative tasks and augment analyst decision-making - Extend and scale our LLM infrastructure (e.g. OpenAI, Anthropic, local models), including prompt engineering, RAG, and evaluation loops - Design safe, observable, and auditable agent behaviors - ensuring reliability in high-sensitivity environments - Evaluate performance across metrics like reasoning, latency, success rate, and hallucination, and iterate based

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