Thomson Reuters
Staff Software Engineer I (Open)
$118K–$220K
United States of America, Eagan, Minnesota +2 · Hybrid · Staff · Full-time · Posted Oct 6, 2026
- Location
- United States of America, Eagan, Minnesota
United States of America, Frisco, Texas
Canada, Toronto, Ontario - Experience
- 8+ years of software engineering experience; demonstrated progression to staff-level or equivalent technical leadership.
- Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
About the job
Sets technical direction for APIs and evaluation systems that give AI agents secure, accurate access to Thomson Reuters’ legal content.
What you'll do
- Define Content Tools architecture, API contracts, retrieval patterns, and shared development and testing infrastructure.
- Establish spec-driven evaluation standards and quality gates for retrieval tools and production workflows.
- Own reliability and operations, lead cross-team technical decisions, and mentor engineers.
What they ask for
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 8+ years of software engineering experience with progression to staff-level or equivalent technical leadership.
- Mastery of Python and strong API design, testing, system design, and security architecture fundamentals.
- Experience designing API-first systems and evaluation frameworks for retrieval or LLM systems; proven system-level reliability ownership.
Nice to have
- Experience building APIs or tools for agentic AI systems, including MCP or similar protocols.
- Search and retrieval engine experience, or background in legal technology or other high-stakes information domains.
Pay
$118,400 USD - $219,800 USD (base salary); $140,600 CAD - $190,600 CAD (base salary)
Tools
Python, FastAPI, Claude Agent SDK, Vespa, MCP (Model Context Protocol), OpenSearch, Elasticsearch, Terraform
AI focus
Builds governed content APIs and retrieval/evaluation infrastructure for AI agents; expects AI-assisted development to be used for most code.
Model-written summary · the original posting is authoritative