Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will work with intelligence analysts to understand their workflows and turn high-impact opportunities into durable technical products. You will design, build, and own AI-powered internal applications, including backend services, APIs, data storage, infrastructure, and user interfaces. You will develop agentic solutions using modern AI models, lead projects from technical design through ongoing support, and iterate based on outcomes.
Requirements
- 6+ years of full-stack software engineering experience building scalable web applications, services, and APIs
- Strong product sense
- Proficiency in Python and/or JavaScript/TypeScript
- Strong backend and systems engineering skills
- Experience building backend systems, working with Postgres/pgvector, Pinecone, and Redis, and designing APIs
- Hands-on experience with AI tools, applications, modern AI models, agentic IDEs, or AI-enabled workflows or prototypes
- Ability to operate independently in ambiguous problem spaces
- Strong communication skills and ability to explain technical trade-offs to semi-technical stakeholders
Responsibilities
- Embed with intelligence analysts to understand goals, constraints, and workflows
- Identify and productize high-leverage opportunities to improve intelligence collection
- Design, build, and own AI-powered internal applications end to end
- Develop custom agentic solutions using state-of-the-art AI models
- Own technical design, architecture, scoping, delivery, iteration, and ongoing support
- Build reliable and scalable systems for analysts
- Evaluate impact and iterate based on outcomes
- Triage internal-tools customer support requests through designated Slack channels as part of on-call rotation
Benefits
- Eligibility to participate in TRM’s equity plan
Hiring Process
Recruiter intro → hiring manager interview → first round of 1–2 interviews → final round of 3–5 interviews → references → offer → onboarding. The process may include a case study, AI skills assessment, and Leadership Principles interview.