Strong engineering background with backend or systems experience (Python preferred)
Hands-on experience with LLMs, agents, and tooling frameworks (e.g., LangChain)
Comfort in optimizing agentic pipelines for AI systems
Thoughtful system design focusing on safety and scalability
High product empathy, considering user impact
Bias towards fast experimentation and iteration
Experience with knowledge graphs or AI safety is a plus
Responsibilities
Architect and implement an agentic framework for tool use, context retrieval, and planning
Build modular agents that automate investigative tasks for analysts
Extend and scale LLM infrastructure, including prompt engineering and evaluation loops
Design safe and auditable agent behaviors for high-sensitivity environments
Evaluate performance metrics like reasoning and latency, iterating based on feedback and telemetry
Contribute to a culture of ethical AI deployment and rapid experimentation
Benefits
Collaborative and inclusive team culture
Focus on rapid issue resolution and efficient knowledge transfer
Opportunities for mentorship and cross-team collaboration
Dynamic work environment that encourages bold initiatives
Strong emphasis on ethical AI practices and user impact
Full Job Description
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
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 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.
Learn about TRM Speed in this position:
Rapid Issue Resolution. TRM Engineers identify and resolve critical onsite issues in minutes to hours, not weeks. We create virtual war rooms, implement fixes, and share lessons with both customer stakeholders and internal teams within 48 hours.
Navigating Bureaucracy. We anticipate and address procedural hurdles, build trust with key stakeholders, and find alternative pathways to approvals. This keeps projects moving even in complex environments.
Efficient Knowledge Transfer. Engineers document and share updates in real time, ensuring the entire team-onsite and remote-has full visibility into plans, blockers, and resolutions. Knowledge sharing sessions and clear documentation reduce friction and accelerate delivery.
About TRM's Engineering Levels:
Engineer: Responsible for helping to define project milestones and executing small decision decisions independently with the appropriate tradeoffs between simplicity, readability, and performance. Provides mentorship to junior engineers, and enhances operational excellence through tech debt reduction and knowledge sharing.
Senior Engineer: Successfully designs and documents system improvements and features for an OKR/project from the ground up. Consistently delivers efficient and reusable systems, optimizes team throughput with appropriate tradeoffs, mentors team members, and enhances cross-team collaboration through documentation and knowledge sharing.
Staff Engineer: Drives scoping and execution of one or more OKRs/projects that impact multiple teams. Partners with stakeholders to set the team vision and technical roadmaps for one or more products. Is a role model and mentor to the entire engineering organization. Ensures system health and quality with operational reviews, testing strategies, and monitoring rigor.
The following represents the expected range of compensation for this role:
Individual pay is determined by skills, qualifications, experience, and location. The compensation details listed in this posting reflect the US base salary only.
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.
Please note - we factor in the different costs for geographies outside the United States.
