AI Agent Engineer - US Remote

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 on user feedback and system telemetry
• Contribute to a culture of high ownership, rapid experimentation, and ethical AI deployment

About The Team

The AI Engineering team operates with a high level of collaboration and interdependence, fostering an inclusive culture where connections extend beyond work. We value diverse personalities and seek someone who is both results-driven and sociable, with strong communication, leadership, and teamwork skills, along with a positive, solutions-oriented mindset.

What We’re Looking For

• Strong engineering background with deep experience in backend or systems work (Python preferred)
• Hands-on experience building with LLMs, agents, and tooling frameworks (LangChain, semantic caches, vector DBs, etc.)
• Comfort working with agentic pipelines and optimizing information flow into AI systems
• Thoughtful approach to system design, with an eye for safety, scalability, and explainability
• High product empathy - you care about how agents impact real users (analysts) and optimize accordingly
• Bias toward experimentation and iteration - you’re excited to try, learn, and ship fast
• Previous experience with knowledge graphs, task orchestration, or AI safety a plus

About TRM

• Rapid Issue Resolution: Identify and resolve critical onsite issues in minutes to hours, not weeks
• Navigate Bureaucracy: Anticipate and address procedural hurdles, build trust with key stakeholders, and find alternative pathways to approvals
• Efficient Knowledge Transfer: Document and share updates in real time, ensuring full visibility into plans, blockers, and resolutions

Compensation

The estimated base salary range for this role is $200,000 - $275,000. Additionally, this role may be eligible to participate in TRM’s equity plan.

Life at TRM

• We move quickly and expect clarity, follow-through, and impact
• We are a high velocity, high ownership team that expects clarity, follow-through, and impact
• We are energized by hard problems, experimentation, and continuous feedback
• We operate with a high level of ownership, adaptability, collaboration, and creative problem-solving
• We navigate ambiguity and adjust course as new information emerges
• We maintain focus and positivity in a fast-moving and intense environment

Literature on AI Fluency

AI Fluency at TRM means using AI to accelerate and reimagine your craft, not just automate surface tasks. We expect every team member to use AI to improve output quality, increase speed, and leverage it in your work.

Leadership Principles

• Impact-Oriented Trailblazer: We put customers first and move with speed, focus, and adaptability. We treat every plan like an experiment – test, ship, measure, and iterate quickly.
• Master Craftsperson: We care deeply about our craft. We balance speed with high standards, own outcomes end-to-end, and invest in getting better every day.
• Inspiring Colleague: We add clarity and energy, not noise. We bring humility, candor, and a one-team mindset — giving and receiving feedback to make the team stronger.

Join Our Mission

At TRM, we care deeply about our craft. We are looking for individuals who want their work to matter, who experiment with speed and rigor, and who take pride in building a safer world for billions of people. If you're excited by TRM's mission but don't check every box, we encourage you to apply — we hire for slope, judgment, and the will to learn fast.

Privacy Policy

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Additional Information

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