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Thomson Reuters

Legal, financial data, and media services

Lead Software Engineer - AI

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeZug, SwitzerlandNo salary listed

About the Job

Requirements

  • Extensive experience architecting and shipping production software systems, including hands-on experience building AI/LLM-powered products or agentic systems, rather than solely classical machine learning or data science.
  • Direct experience building with modern large language model application programming interfaces, agent frameworks or software development kits, or agent-to-tool integration protocols.
  • A track record of setting technical direction across multiple concurrent initiatives, rather than delivering only one project end-to-end.
  • Strong backend engineering fundamentals, including distributed systems design, service architecture, and cloud infrastructure.
  • Experience designing for production reliability and observability, including monitoring, evaluation pipelines, incident response, and quality regression detection.
  • Demonstrated ability to mentor senior engineers and influence technical culture and practices.
  • Comfort operating with high autonomy on a fast-moving, senior-heavy team that builds with AI-native or agentic engineering practices.

Responsibilities

  • Set technical architecture and direction across the team's highest-priority initiatives, spanning core agent infrastructure, new internal tooling, and production reliability.
  • Provide hands-on technical leadership across the team's highest-priority initiatives, flexing between them rather than remaining within a single fixed workstream.
  • Architect and build production AI agent systems using modern large language model application programming interfaces, agent software development kits, and orchestration or runtime infrastructure, designed to scale and integrate with existing platform services.
  • Design agent observability and evaluation practices, including tracing, automated evaluations, and quality or drift detection, to catch regressions in agent behavior before they reach customers.
  • Advance the team's deployment and production operations for AI agents, including progressive or feature-flagged rollout and earlier-stage quality signals, to improve release speed and safety.
  • Drive cross-cutting design reviews and technical decisions, including RFCs and ADRs, to keep systems coherent as multiple initiatives progress in parallel.
  • Mentor and raise the technical bar for a senior engineering team, including its use of AI-native, agentic development practices.
  • Partner with product and engineering leadership to translate strategic priorities into system architecture and sequencing decisions.

Desired Qualifications

  • Experience leading architecture for developer-facing platforms, plugin or extension systems, or integration ecosystems.
  • Familiarity with progressive delivery practices, including feature flagging, phased rollout, or blue/green deployment at scale.
  • Experience advancing software delivery practices, including progressive delivery, shift-left quality and testing, and engineering discipline reflected in deployment frequency, lead time, and change failure rate.
  • Experience with managed agent runtime infrastructure, such as AWS Bedrock AgentCore or similar.
  • Domain expertise in legal, regulated, professional-services, or other fiduciary domains.

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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