About the job
Join Us in Building a Safer World
At TRM Labs, we are at the forefront of blockchain analytics and AI solutions. Our mission is to empower law enforcement, national security agencies, financial institutions, and cryptocurrency companies to detect, investigate, and combat cryptocurrency-related fraud and financial crimes. Our advanced blockchain intelligence and AI platforms provide capabilities to trace funds, identify illicit activities, build solid cases, and construct a comprehensive picture of emerging threats. Trusted globally, TRM is dedicated to fostering a safer and more secure world.
The AI Engineering Team is focused on developing next-generation AI applications, emphasizing Large Language Models (LLMs) and agentic systems. We aim to create resilient pipelines, high-performance infrastructures, and operational tools that allow for the swift, safe, and scalable deployment of AI systems.
We handle petabyte-scale data pipelines, serve models with millisecond response times, and ensure the observability and governance necessary to make AI production-ready. Our team is committed to evaluating and integrating cutting-edge tools within the LLM and agent space, including open-source stacks, vector databases, evaluation frameworks, and orchestration tools that accelerate TRM's innovation.
Your Impact:
- Design and implement a robust agentic framework that facilitates tool utilization, context retrieval, memory, and planning.
- Create intelligent, modular agents to automate investigative tasks and enhance analyst decision-making.
- Extend and scale our LLM infrastructure (e.g., OpenAI, Anthropic, local models), focusing on prompt engineering, retrieval-augmented generation, and evaluation loops.
- Develop safe, observable, and auditable agent behaviors to ensure reliability in sensitive environments.
- Assess performance across metrics such as reasoning, latency, success rate, and hallucination, iterating based on user feedback and telemetry.
- Foster a culture of ownership, rapid experimentation, and ethical AI deployment.

