Engineering Manager, AI

Thomson Reuters•Eagan, MN

2d•Hybrid

About The Position

The Engineering Manager will build and lead a team of software engineers, including Senior and Staff-level engineers, delivering full-stack products, AI-enabled features, and services for the next generation of Westlaw. The team will create agentic legal research experiences and retrieval services grounded in trusted legal content. This is a hands-on technical leadership role involving architecture, engineering standards, coding, prototyping, code review, and production issue resolution. The manager will guide the use of agentic systems, retrieval-augmented generation (RAG), large language models (LLMs), and AI-assisted development to deliver trustworthy, scalable, secure, and high-performing solutions for legal professionals worldwide. The role oversees scalable user interfaces, backend services, RESTful APIs, and cloud-native solutions on AWS. It sets technical practices and DevOps expectations, including team ownership of build, deployment, monitoring, and reliability. The manager establishes quality and security practices throughout development, evaluates emerging AI tools and retrieval patterns for production readiness, and leads the responsible use of AI agents across the engineering lifecycle. The role also manages hiring and development, partners with Product, Design, and other stakeholders, and delivers against product roadmaps through incremental delivery and measurable outcomes. The position is part of Thomson Reuters’ Global Westlaw Engineering organization, which builds and operates the technology behind Westlaw. The posting is for proactive recruitment and may be used to fill current or future vacancies. The role uses a flexible hybrid work model for office-based roles.

Requirements

At least 8 years of hands-on software engineering experience across front-end and back-end, building scalable web applications.
At least 3 years of experience managing engineering teams.
Track record leading teams that ship and operate production-grade full-stack systems at scale, with secure coding and reliability practices.
Hands-on technical leadership through architecture discussions, design decisions, code reviews, and prototyping.
Hands-on experience building with LLMs in production or serious prototypes, such as RAG, prompt and context design, evaluation, or agent workflows.
Daily use of AI coding tools, such as GitHub Copilot, Cursor, or Claude Code.
Experience leading or working hands-on in a team that builds and uses AI agents, with strong review, quality, and security practices.
Clear understanding of RESTful API design, including resource modeling and URI design; HTTP methods and status codes; idempotency; pagination, filtering, and versioning; authentication and authorization; consistent error handling; and API documentation such as OpenAPI/Swagger.
Strong proficiency in Python and in designing and building RESTful APIs.
Working proficiency in React or a similar modern UI framework, such as Angular or Vue, and experience with TypeScript and Node.js.
Strong knowledge of AWS architecture and services, with experience in DevOps, CI/CD pipelines, and infrastructure as code.
Success hiring, coaching, mentoring, and developing engineers, including Senior and Staff levels.
Experience partnering with Product, Design, and cross-functional leaders to set strategy and execute.
Excellent communication skills, including setting clear goals, giving direct feedback, and aligning stakeholders.
Comfort working in a fast-moving, ambiguous environment and making data-driven decisions as priorities evolve.
Strategic mindset and ability to align technical decisions with business goals.
Bachelor’s degree in computer science, engineering, or a related discipline, or equivalent practical experience.

Nice To Haves

Experience shipping AI-driven or agentic systems in production, including LLM orchestration, RAG and information retrieval, agent frameworks, and tool protocols such as MCP, using LLM APIs such as OpenAI or Anthropic reliably at scale.
Experience with agent evaluation, including testing, benchmarking, and monitoring agent behavior.
Experience with Python frameworks such as Django, Flask, or FastAPI.
Background managing mixed teams of front-end, back-end, and software/AI engineers.
Track record of changing team mindsets and helping engineers adopt new tools and ways of working.
Exposure to legal or other regulated professional domains.
AWS certifications, such as Solutions Architect or DevOps Engineer.

Responsibilities

Build and lead a team of software engineers, including Senior and Staff levels; own hiring, onboarding, performance management, and professional development.
Develop engineers’ software fundamentals and expertise in information retrieval and agentic system design.
Foster empowered ownership, sound technical decision-making, reliable production operations, and continuous learning.
Lead hands-on through coding, code review, prototyping, architecture discussions, and resolution of critical production issues.
Communicate complex technical concepts and trade-offs clearly to stakeholders.
Oversee development of scalable user interfaces, backend services, and RESTful APIs.
Drive generative AI and LLM integration initiatives.
Shape architecture, engineering standards, coding practices, and code review processes.
Champion DevOps practices, with engineers owning build, deployment, monitoring, and reliability, supported by automation and CI/CD.
Ensure functional and non-functional requirements are met, including performance, scalability, reliability, security, and maintainability.
Embed rigorous testing, secure coding, and continuous quality evaluation throughout development.
Design and manage cloud-native solutions on AWS.
Evaluate and integrate emerging tool protocols, such as MCP, and retrieval patterns with attention to production readiness and operational implications.
Make AI-assisted and agent-driven development a team norm; monitor and optimize token consumption to balance productivity, quality, and cost.
Lead feature development using AI agents, establishing practices for task specification, human review of agent-generated code, and accountability for shipped work.
Apply AI to code generation, code review, test automation, and quality evaluation with safeguards for security, data handling, and responsible use.
Define measures for the impact of AI and agents on delivery speed, code quality, and defect rates.
Define and maintain secure engineering processes for the team building and delivering flagship legal research products.
Deliver solutions aligned with product roadmaps through incremental delivery; manage dependencies and track success metrics.
Stay current with developments in AI, cloud computing, and software engineering and incorporate relevant advances into team practices.
Partner with Product, Design, and cross-functional leaders to set strategy and execute against it.

Benefits

Flexible vacation and paid time off, including sick and safe time.
Two company-wide Mental Health Days off annually.
Access to the Headspace app.
Retirement savings and a competitive 401(k) plan with company match.
Tuition reimbursement.
Employee incentive programs and potential annual bonus based on enterprise and individual performance.
Resources for mental, physical, and financial wellbeing.
Health insurance.
Dental insurance.
Vision insurance.
Disability insurance.
Life insurance.
Paid holidays.
Parental leave.
Sabbatical leave.
Flexible Spending and Health Savings Accounts.
Fitness reimbursement.
Employee Assistance Program.
Commuter benefits.
Adoption and surrogacy assistance.
Employee Stock Purchase Plan.
Two paid volunteer days off annually.
Flexible hybrid work arrangements for office-based roles, including work from anywhere for up to 8 weeks per year.
Career development and skills-development programming.
Optional hospital, accident and sickness insurance, paid entirely by the employee.
Optional life and AD&D insurance, paid entirely by the employee.
Group Legal Identity Theft Protection benefit, paid entirely by the employee.
Access to a 529 Plan.