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Software Engineer, AI Product Engineering

Job in Ann Arbor, Washtenaw County, Michigan, 48113, USA
Listing for: Thomson Reuters
Full Time position
Listed on 2026-09-15
Job specializations:
  • Software Development
    Backend Developer, Software Architect, AI Engineer (Applied/Software), Python
Salary/Wage Range or Industry Benchmark: 127400 - 236600 USD Yearly USD 127400.00 236600.00 YEAR
Job Description & How to Apply Below

Thomson Reuters is looking for a
Staff Software Engineer, AI Product Engineering
to help shape and build the next generation of AI-powered software for tax and accounting professionals. You will join the CoCounsel for Tax & Accounting organization, working in a fast-moving, product-focused environment that combines startup-style ownership with the scale and resources of Thomson Reuters.

This is a highly hands-on Staff-level engineering role for someone who thrives in
greenfield and 01 product development
. You will be expected to take ambiguous product and technical problems, define the right architecture, build critical parts of the solution yourself, and help guide other engineers from prototype through production.

This is a hybrid role, with opportunities based in
New York City, Minneapolis-St. Paul, or Toronto
. Candidates should be comfortable working onsite as part of the team's hybrid schedule. Final interviews may also be conducted onsite at the hiring hub associated with the candidate's location.

About the Role

As a Staff Software Engineer, AI Product Engineering, you will:

  • Own greenfield and 01 AI systems, taking ambiguous product problems from technical discovery and architecture through implementation, production launch, monitoring, and iteration.

  • Design and build production backend services using Python, FastAPI, PostgreSQL, and AWS.

  • Build and evolve AI-native applications incorporating large language models, AI agents, orchestration, retrieval, tool/function calling, and real-time AI workflows.

  • Integrate models and services from providers such as OpenAI, Anthropic, and other foundation‑model platforms.

  • Design scalable APIs, data models, asynchronous workflows, and distributed services for high-volume, production-grade AI applications.

  • Make and influence architectural decisions across reliability, scalability, latency, observability, security, testing, failure handling, and maintainability.

  • Establish reusable engineering patterns and technical standards that improve consistency and velocity across multiple teams or work streams.

  • Evaluate AI behavior in production and build mechanisms for quality measurement, experimentation, evaluation, guardrails, and continuous improvement.

  • Partner closely with Product and Design to translate complex customer problems into simple, scalable technical solutions.

  • Provide technical leadership across complex, cross-functional initiatives while remaining hands‑on in design, implementation, debugging, and code review.

  • Mentor engineers, raise the technical bar, and help teams make sound architectural and engineering trade‑offs.

  • Identify technical risks early and drive solutions across multiple systems or teams.

About You

You are a strong fit for this role if you have:

  • Significant software engineering experience building and operating large‑scale, production‑grade backend systems.

  • Strong, recent hands‑on development experience with Python.

  • Production experience with backend frameworks such as FastAPI, Flask, or Django, with FastAPI strongly preferred.

  • Experience designing APIs, backend services, data models, asynchronous systems, and distributed architectures.

  • Experience with relational databases such as PostgreSQL and building production systems on a major cloud platform; AWS experience is strongly preferred.

  • Demonstrated experience personally designing, building, and launching greenfield or 01 products and systems, with clear ownership from architecture through production.

  • Experience making architecture decisions that affect multiple systems, teams, or major product capabilities.

  • Strong system‑design skills with the ability to reason through scalability, reliability, performance, failure modes, and operational trade‑offs.

  • Experience taking software through the full…

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