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Job Description

Senior AI Engineer role on Thomson Reuters’ agent platform team, building and deploying AI agent systems end-to-end using AI-native engineering practices.

Responsibilities

  • Design and deliver complex AI agent systems end-to-end, including multi-component pipelines, tool integrations, and multi-step reasoning for initiatives you own
  • Build production AI agent systems using modern LLM APIs, agent SDKs, and orchestration/runtime infrastructure; integrate cleanly with existing platform services
  • Advance agent observability and evaluation through tracing, automated evals, and quality or drift detection to catch regressions before they reach customers
  • Apply and extend progressive delivery practices such as feature-flagged rollout and earlier-stage quality signals to improve release velocity and stability
  • Participate in cross-cutting design discussions and technical decisions via RFCs/ADRs, ensuring new systems fit into the overall architecture
  • Mentor engineers and help build technical culture by modeling effective AI-native, agentic development practices
  • Collaborate with product and engineering peers to translate requirements into solid technical designs

Requirements

  • Proven experience architecting and shipping production software systems, with hands-on work building AI/LLM-powered products or agentic systems (not limited to classical ML/data science)
  • Direct experience building with modern LLM APIs, agent frameworks/SDKs, or agent-to-tool integration protocols
  • Ability to own complex technical projects end-to-end, from design through production delivery
  • Strong backend engineering foundation: distributed systems design, service architecture, and cloud infrastructure
  • Experience with production reliability and observability: monitoring, evaluation pipelines, incident response, and quality regression detection
  • Ability to mentor other engineers and contribute to a strong technical culture
  • Comfort operating with high autonomy on a senior-heavy, fast-moving team using AI-native/agentic engineering practices

Technologies

  • LLM APIs
  • Agent SDKs
  • Orchestration/runtime infrastructure
  • Feature flagging
  • Tracing
  • Automated evals
  • Monitoring
  • AWS Bedrock AgentCore

Location and Salary

  • Location: Eagan, MN (hybrid)
  • Salary range: USD 100,000 - 204,200 per year

Benefits

  • Hybrid Work Model
  • Flex My Way: flexible hybrid working, work from anywhere for up to 8 weeks per year
  • Grow My Way: programming and skills-first approach
  • Comprehensive benefit plans including flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing
  • Social Impact Institute: two paid volunteer days off annually, plus opportunities for pro-bono consulting and ESG initiatives
  • US benefits package including market competitive health, dental, vision, disability, and life insurance; competitive 401k plan with company match
  • Paid time off including paid holidays (including two company mental health days off), parental leave, sabbatical leave
  • Optional hospital, accident and sickness insurance paid 100% by the employee
  • Optional life and AD&D insurance paid 100% by the employee
  • Flexible Spending and Health Savings Accounts
  • Fitness reimbursement
  • Access to Employee Assistance Program
  • Group Legal Identity Theft Protection benefit paid 100% by employee
  • Access to 529 Plan
  • Adoption & Surrogacy Assistance
  • Access to Employee Stock Purchase Plan
  • Ability to receive an Annual Bonus based on a combination of enterprise and individual performance

Preferred Qualifications

  • Experience with developer-facing platforms, plugin/extension systems, or integration ecosystems
  • Familiarity with progressive delivery practices (feature flagging, phased rollout, blue/green deployment) at scale
  • Experience with managed agent runtime infrastructure (for example, AWS Bedrock AgentCore or similar)
  • Domain expertise in legal, regulated, professional-services, or other fiduciary domains is a plus, but not required

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