Job Description Thomson Reuters products power the professionals shaping the world. Confirmation is the industry-leading audit confirmation platform, connecting audit firms, their clients, and thousands of responding institutions to securely verify balances and transactions with speed and certainty.

Job Description Thomson Reuters products power the professionals shaping the world. Confirmation is the industry-leading audit confirmation platform, connecting audit firms, their clients, and thousands of responding institutions to securely verify balances and transactions with speed and certainty. As a Staff Software Engineer – AI on the Confirmation Product Engineering team, you will be a hands‑on technical leader building and delivering production platform and AI capabilities . This role requires strong production C#/.NET engineering experience , along with Python experience for AI/ML development and integration . We are looking for an engineer who has personally built and delivered AI features into production as part of enterprise software products. This is not a pure architecture, research, data science, or proof‑of‑concept role. You will remain deeply hands‑on in the code while providing Staff‑level technical leadership. You will design and build C#/.NET backend and distributed systems and use Python to develop and integrate AI/ML capabilities , including large language model (LLM)-powered applications, AI agents, orchestration, retrieval, and document understanding. You will partner with Principal Engineers and cross‑functional teams to establish AI engineering patterns, develop Model Context Protocol (MCP) servers and agent‑based capabilities, and build reliable and scalable AI infrastructure.

Key Responsibilities





- Architect, develop, and deliver production backend and platform services using C#/.NET, PostgreSQL, AWS, microservices, and distributed‑system patterns.
- Build production AI/ML capabilities using Python, including LLM integration, AI agents, orchestration, retrieval, and multi‑step AI workflows.
- Lead hands‑on AI engineering initiatives across product and infrastructure, including agent‑based workflows, retrieval systems, and AI‑assisted document processing.
- Build and evolve AI orchestration capabilities, including routing, tool calling, MCP servers, multi‑step workflows, safety controls, guardrails, evaluation, and resilient error handling around third‑party LLMs.
- Design reliable, scalable, high‑throughput distributed systems and AI workloads, incorporating caching, queuing, rate limiting, model failover, observability, resilience, and cost/performance optimization.
- Develop retrieval and data capabilities using document search, vector stores, embeddings, semantic search, and indexing strategies for large‑scale audit and confirmation use cases.
- Provide hands‑on Staff‑level technical leadership by setting technical direction, influencing engineering standards, mentoring engineers, and continuing to personally design, code, build, and deliver production systems.

Required Qualifications





- Bachelor’s degree in Computer Science, Computer Engineering, a related field, or equivalent qualified experience.
- 7+ years of progressive software engineering experience, including hands‑on development, architecture, and delivery of large‑scale production systems.
- Strong, recent, hands‑on C#/.NET production development experience, including building backend services and APIs using C#/.NET and ASP.NET Core or similar technologies.
- Hands‑on Python experience for AI/ML system development, including model integration, AI orchestration, APIs, data pipelines, or comparable production use cases.
- Demonstrated experience personally building and delivering AI/ML features into production, including LLM‑powered applications, AI agents, retrieval/RAG, orchestration, or comparable AI‑native capabilities.
- Strong hands‑on platform and distributed‑systems engineering experience, including microservices, system integration, data modeling, REST or GraphQL APIs, relational databases, observability, resilience, scalability, and performance optimization.
- Experience implementing appropriate AI safety controls, guardrails, evaluation, reliability, and production operational practices.
- Proven experience leading complex engineering initiatives from architecture and hands‑on implementation through deployment, rollout, and long‑term production operation.
- Proven ability to operate as a hands‑on Staff‑level technical leader, providing technical direction and mentoring engineers while continuing to actively design, code, build, and deliver production software.
- Strong communication and cross‑functional collaboration skills with the ability to partn

📌 Staff Software Engineer (Canada)
🏢 Thomson Reuters
📍 Canada