# Senior Software Engineer AI at Thomson Reuters

Thomson Reuters is hiring a Senior Software Engineer AI. It pays $118k-$220k a year and Level rates it Builds AI ●●●●; you can [apply on Thomson Reuters](https://jobsbylevel.com/go/45cf4789-1880-4512-a971-bb27a095a7b7?utm_medium=ai-agent).

AI Level 4, AI centrality 86 out of 100. United States of America, Eagan, Minnesota.

## Details

- Company: [Thomson Reuters](https://jobsbylevel.com/companies/thomson-reuters)
- AI level: AI Level 4 (score 86 out of 100)
- Location: United States of America, Eagan, Minnesota
- Salary: $118k-$220k
- Posted: November 13, 2026
- Apply: https://jobsbylevel.com/go/45cf4789-1880-4512-a971-bb27a095a7b7?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-software-engineer-ai-at-thomson-reuters-2327b1

## Prepare for this job

The job page lists 5 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/senior-software-engineer-ai-at-thomson-reuters-2327b1

## Description

Job Description Senior Software Engineer, AI Are you passionate about transforming the future of legal research with AI? Join our Global Westlaw Engineering organization and help shape the next generation of intelligent legal research solutions. The Global Westlaw Engineering organization builds and operates the technology that powers Westlaw, the world’s leading legal research platform. Our teams develop innovative products and fiduciary-level, AI-based solutions that help legal professionals find trusted answers, uncover insights, and make confident decisions faster. Working across engineering, AI, data, platform, and product disciplines, we deliver secure, scalable, and intelligent experiences for customers around the globe. As a Senior Software Engineer, AI, you will be a key technical contributor on a team that delivers the full-stack products, AI-enabled features, and services behind Westlaw’s next generation of experiences. You will build agentic legal research experiences and the retrieval services that ground them in trusted legal content. You will be deeply hands-on, designing and writing production code, contributing to architecture, and raising the engineering bar for your team. You will build with agentic systems, retrieval-augmented generation (RAG), and large language models (LLMs), and use AI-assisted development as a core way of working so you can deliver intelligent, trustworthy, and high-performing solutions for legal professionals worldwide. Key Responsibilities Technical Ownership · Design, build, and ship scalable user interfaces, backend services, and RESTful APIs. · Build GenAI and LLM integrations, including agentic workflows, prompt and context design, and retrieval services grounded in trusted legal content. · Contribute to architecture, engineering standards, coding practices, and code review, with a focus on deep technical ownership. · Own your work through to reliable production operations, including build, deployment, monitoring, and reliability, supported by automation and CI/CD. · Ensure delivery meets functional and non-functional requirements, including performance, scalability, reliability, security, and maintainability. · Embed quality and security into every stage of development, with rigorous testing, secure coding practices, and continuous evaluation of quality. · Design and build cloud-native solutions on AWS. · Evaluate and integrate emerging tool protocols (such as MCP) and retrieval patterns, with a clear understanding of production readiness and operational implications. · Resolve critical production issues and drive root-cause fixes. AI-Enabled Engineering · Use AI-assisted and agent-driven development daily, and monitor and optimize token consumption to balance productivity, quality, and cost. · Deliver features using AI agents, applying clear task specification, careful human review of agent-generated code, and accountability for what ships. · Apply AI across the engineering lifecycle, including code generation, code review, test automation, and quality evaluation, with guardrails for security, data handling, and responsible use. · Help measure the impact of AI and agents on delivery speed, code quality, and defect rates. · Build and apply evaluation practices for agents, including testing, benchmarking, and monitoring agent behavior. Collaboration and Mentorship · Mentor and coach engineers, sharing knowledge in information retrieval, agentic system design, and AI-assisted development. · Help shift team mindsets by modeling continuous learning and introducing new tools, practices, and ways of working. · Partner with Product, Design, and cross-functional teams to translate requirements into well-designed solutions. · Translate complex technical concepts and trade-offs into clear terms for stakeholders. · Delivery · Deliver solutions aligned with product roadmaps through incremental delivery, managing dependencies and tracking success metrics. · Follow and help improve secure

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