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Thomson Reuters

Legal, financial data, and media services

Engineering Manager - AI

Engineering LeadershipConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 8 years of hands-on software engineering experience across front-end and back-end, building scalable web applications, and at least 3 years managing engineering teams.
  • A track record of leading teams that ship and operate production-grade full-stack systems at scale, including secure coding practices and reliability, and of staying hands-on through architecture discussions, design decisions, code reviews, and prototyping.
  • Hands-on experience building with large language models in production or serious prototypes, such as retrieval-augmented generation, prompt and context design, evaluation, or agent workflows, and 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 practices for review, quality, and security.
  • Clear understanding of RESTful API design principles, including resource modeling and URI design, correct use of HTTP methods and status codes, idempotency, pagination, filtering and versioning, authentication and authorization, consistent error handling, and API documentation such as OpenAPI or 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 in 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 against it.
  • Ability to set clear goals, give direct feedback, and align stakeholders.
  • Ability to operate in a fast-moving, ambiguous environment and make data-driven decisions as priorities evolve.
  • Strategic mindset and ability to ensure technical decisions align with business goals.
  • A Bachelor's degree in computer science, engineering, or a related discipline, or equivalent practical experience.

Responsibilities

  • Build and lead a team of software engineers, including Senior and Staff levels, owning hiring, onboarding, performance management, and professional development, with a focus on deep technical ownership.
  • Develop engineers with strong software fundamentals and domain expertise in information retrieval and agentic system design.
  • Foster empowered ownership so engineers define problems, make sound technical decisions, and carry work through to reliable production operations.
  • Shift team mindsets and build a culture of continuous learning, helping engineers adopt new tools, practices, and ways of working.
  • Lead by example as a hands-on technical manager by writing and reviewing code, prototyping solutions, and resolving critical production issues.
  • Translate complex technical concepts and trade-offs into clear terms for stakeholders.
  • Oversee development of scalable user interfaces, backend services, and RESTful APIs.
  • Drive generative AI and large language model integration initiatives.
  • Shape architecture, engineering standards, coding practices, and code review processes.
  • Champion a DevOps-first mindset in which engineers own 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 at every stage of development through rigorous testing, secure coding practices, and continuous quality evaluation.
  • Design and manage cloud-native solutions on AWS.
  • Evaluate and integrate emerging tool protocols such as MCP and retrieval patterns, considering production readiness and operational implications.
  • Model AI-assisted and agent-driven development as a team norm, and monitor and optimize token consumption to balance productivity, quality, and cost.
  • Lead feature development using AI agents, setting practices for task specification, human review of agent-generated code, and accountability for shipped work.
  • 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.
  • Define how the team measures the impact of AI and agents on delivery speed, code quality, and defect rates.
  • Define and maintain secure engineering processes for the team that builds and delivers flagship legal research products.
  • Deliver solutions aligned with product roadmaps through incremental delivery, managing dependencies and tracking success metrics.
  • Stay current with developments in AI, cloud computing, and software engineering, and bring them into the team's practices.

Desired Qualifications

  • Experience shipping AI-driven or agentic systems in production, such as LLM orchestration, RAG and information retrieval, agent frameworks, and tool protocols such as MCP, using LLM APIs such as OpenAI and 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.
  • A 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.

About the Company

Thomson Reuters

Legal, financial data, and media services

Thomson Reuters provides intelligent information and professional services for law, tax, finance, and media. It serves law firms, corporations, government agencies, and financial institutions with platforms like legal research (Westlaw), tax software (UltraTax CS), financial market data, and news services. These products are accessed through subscription-based platforms, ensuring ongoing updates and a steady revenue stream. The company also monetizes through advertising on media platforms and data analytics sales. It distinguishes itself by offering a broad, integrated suite of industry-specific tools combined with AI, cognitive computing, and machine learning to improve accuracy, efficiency, and predictive analytics in research and data insights. Its goal is to be a trusted partner that helps professionals make informed decisions by delivering reliable information and decision-ready tools while pursuing responsible, values-driven initiatives.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1851

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