Staff Software Engineer, AI Product Engineering

Thomson Reuters is looking for aStaff Software Engineer AI Product Engineeringto 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 ingreenfield 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 inNew York City MinneapolisSt. Paul or Toronto. Candidates should be comfortable working onsite as part of the teams hybrid schedule. Final interviews may also be conducted onsite at the hiring hub associated with the candidates 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 workstreams.

• 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 lifecycle including architecture implementation deployment observability debugging incident response and production iteration.

• Demonstrated ability to influence technical direction without relying on formal authority.

• Strong communication skills and experience partnering effectively across Engineering Product Design AI/ML and other technical stakeholders.

• Ability to operate effectively in ambiguous fast-moving environments and turn incomplete requirements into clear technical direction.

• Hands-on production experience building generative AI or AI-native applications is strongly preferred.

• Experience with LLM-powered agents agent orchestration tool/function calling RAG embeddings vector search retrieval systems or real-time AI interactions is preferred.

• Experience integrating commercial or open foundation models including OpenAI Anthropic or similar providers is preferred.

• Experience building customer-facing SaaS or product software in a startup scale-up or similarly high-ownership environment is preferred.

• Experience with Docker Kubernetes CI/CD infrastructure as code observability and modern cloud-native engineering is preferred.

• Exposure to TypeScript or modern frontend frameworks is helpful but not required.