About the job
Contribute to a Safer World.
At TRM Labs, we specialize in cutting-edge blockchain analytics and AI solutions designed to assist law enforcement, national security agencies, financial institutions, and cryptocurrency businesses in identifying, investigating, and preventing crypto-related fraud and financial crimes. Our advanced blockchain intelligence and AI platforms provide essential tools for tracing the flow of funds, detecting illicit activities, building comprehensive cases, and mapping out potential threats. Trusted by top agencies and corporations worldwide, TRM Labs empowers a more secure and reliable environment for everyone.
Join our AI Engineering Team, dedicated to pioneering next-generation AI applications with a focus on Large Language Models (LLMs) and agentic systems. We strive to develop high-performance infrastructure, robust pipelines, and operational tools that facilitate the rapid, safe, and scalable deployment of AI systems.
Our work involves managing petabyte-scale data pipelines, delivering models with millisecond latency, and ensuring the observability and governance required for production-ready AI. We actively evaluate and integrate state-of-the-art tools in the LLM and agent domains—ranging from open-source stacks to vector databases and orchestration tools—to enhance TRM's innovation capabilities.
Your Impact:
Design and implement a robust agentic framework that supports tool usage, context retrieval, memory, and planning.
Create intelligent, modular agents that automate investigative responsibilities and enhance analyst decision-making.
Expand and optimize our LLM infrastructure (e.g., OpenAI, Anthropic, local models), including prompt engineering, RAG, and evaluation cycles.
Develop safe, observable, and auditable agent behaviors to ensure reliability in sensitive environments.
Assess performance based on metrics like reasoning, latency, success rate, and hallucination, iterating improvements based on user feedback and telemetry data.
Foster a culture of ownership, rapid experimentation, and ethical AI practices.
Qualifications:
Solid engineering background with significant experience in backend or systems development (Python preferred).
Practical experience in building LLMs, agents, and tooling frameworks (LangChain, semantic caches, vector databases, etc.).
Proficient with AI operational tooling and frameworks, ensuring effective deployment and management.

