Principal Software Engineer - AI Platform & Architecture

Thomson Reuters products power the professionals who are shaping the world. Our platforms drive legal, tax, accounting and audit products, including Cloud Audit Suite – a connected set of products spanning Engagement Manager, Guided Assurance, and Confirmation. As a Principal Software Engineer for Cloud Audit Suite, you will be the technical architect and hands‑on design leader for our product platforms, integrating multiple products and technology stacks. You will also help drive our shift to an engineering‑led, AI‑native organization, one where AI writes much of the code and engineers stay in the loop to provide judgment, architecture, and direction where it matters most. About the role Own the architecture, system design and AI strategy: You will be the principal engineer responsible for the architecture and system design of Cloud Audit Suite and new integrations to Confirmation and CoCounsel Audit via agents, APIs, MCP connections and shared components and repositories. Drive AI strategy for Cloud Audit Suite and help deliver the company's AI strategy. Set the technical direction for how we build MCP servers, design agents, find novel uses of LLMs, run experimentation, and stand up scalable solutions. Your decisions will influence multiple product lines, not just a single feature. Work at real production scale: Build and evolve systems that operate over millions of documents, structured and unstructured data, audit compliance rules, and thousands of concurrent AI interactions from accountants doing time‑sensitive work. Small teams, big surface area: Interact and lead across several teams of engineers, product, UX design and AI Labs partners to research, design and ship products quickly, with direct access to product leadership and customers. What you'll do Technical leadership and cross‑functional influence Partner with the CoCounsel Audit Principal Engineer to determine the best ways to integrate Cloud Audit Suite (CAS) and CoCounsel Audit via MCP servers and tools, shared APIs, and agent‑to‑agent (A2A) integrations. Lead multiquarter initiatives that cut across product engineering, product, labs, UX design and infrastructure/operations teams. Mentor staff and senior engineers, raising the bar on system design, code quality, and AI‑native engineering practices, including AI‑assisted and AI‑generated development with humans in the loop, across the org. Be the expert in new model capabilities and scalable AI integration strategies, collaborating closely with AI/ML engineers, researchers, designers, and PMs to translate industry improvements into reliable, user‑facing workflows that accountants trust. Help shape the team's roadmap, technical strategy, and engineering culture – from experimentation practices to design, coding, testing, rollout, support and post‑mortems. Design and own AI‑first backend systems Own the end‑to‑end architecture and design of backend services (C#/.NET, Python, FastAPI, PostgreSQL, AWS, Vercel) that integrate and orchestrate across heterogeneous systems and technology stacks, powering generative AI agents, complex workflows and document‑centric experiences. Build and evolve AI orchestration: routing, tool calling, MCP servers, multistep workflows, safety and guardrails, and robust error handling around third‑party LLMs (OpenAI, Anthropic, and others). Scale, reliability, compliance and performance Design for high‑throughput, low‑latency AI workloads: caching, queuing, rate‑limiting, model failover, and cost/performance trade‑offs. Work with large‑scale data: millions of documents, retrieval and search, vector stores, and indexing strategies tailored to tax, account and audit use cases. Help establish and refine SLOs, observability, and incident response for AI systems that must be correct, auditable, and trustworthy in professional workflows. About You You are a fit for the position of Principal Software Engineer if your background includes: Required Experience & Skills Bachelor’s Degree in Computer Science, Computer Engineering, Related Field, or Equivalent Experience 8–10+ years of experience in full‑stack application development, including hands‑on architecture and design leadership for large‑scale systems, building scalable web services and APIs. C#, .NET expertise and experience with production systems using frameworks like ASP.NET Core (or similar), relational databases (SQL Server, PostgreSQL or equivalent), and a major cloud provider (AWS preferred, Azure). Experience with Python in AI/ML system development, including model integration, data pipelines, or API‑based orchestration. Familiarity with actor model patterns and frameworks (Orleans, Akka, etc.) for resilient, message‑driven distributed architectures. Experience architecting and implementing accessible front‑end solutions, including: JavaScript, TypeScript, HTML, CSS; experience with modern JavaScript frameworks, e.g., Angular, React, etc. Demonstrated experience and passion for AI systems and new engineering paradigms: LLMs, agents, retrieval, or similar – you care about what “AI‑native” software should look like and know what guardrails to put in place. Strong background in distributed systems and cross‑system integration: data modeling, API contracts, integrating across heterogeneous services and technology stacks, observability, resilience patterns, and performance tuning under load. Proven track record owning large, complex projects end‑to‑end: architecture, execution, rollout, and long‑term support and maintenance. Excellent communication skills and the ability to partner with product, design, UX design and ML teams in a fast‑moving environment. Preferred Skills & Experience Experience designing and implementing CI/CD pipelines (e.g., GitHub Actions) Hands‑on experience integrating LLM APIs (e.g., OpenAI, Anthropic) into production applications, including prompt/response management, cost controls, and safety considerations. Experience with AI‑adjacent infrastructure: vector databases, embeddings, semantic search, or custom retrieval pipelines. Experience having direct interaction and communications with customers. Opinions and experience around automated testing, reliability, and release practices for systems with nondeterministic model behavior. Prior experience in domains where correctness, auditability, and compliance matter (fintech, tax, audit, legal, or similar), or strong interest in applying AI in those contexts. Benefits Hybrid Work Model: Flexible hybrid working environment (2–3 days a week in the office depending on the role) and digital and physical connectivity. Flexibility & Work‑Life Balance: Flex My Way policies supporting personal responsibilities, work from anywhere for up to 8 weeks per year. Career Development and Growth: Continuous learning and skill development programs, Grow My Way programming and skills‑first approach. Industry Competitive Benefits: Flexible vacation, mental health days off, Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for wellbeing. Culture: Inclusion and belonging, flexibility, work‑life balance, and values of customer obsession, win‑or‑lose culture, learning fast, and stronger together. Social Impact: Paid volunteer days off annually and ESG initiatives. Equal Employment Opportunity Thomson Reuters is an Equal Employment Opportunity Employer. We comply with local laws that require upfront disclosure of the expected pay range for a position. We offer a comprehensive benefits package, including health, dental, vision, disability, and life insurance programs, competitive 401(k) plan with company match, and additional benefits such as flexible spending accounts, fitness reimbursement, Employee Assistance Program, commuter benefits, and tuition reimbursement. We provide reasonable accommodations for applicants with disabilities, and are committed to an inclusive workplace. For more information about Thomson Reuters, visit thomsonreuters.com. #J-18808-Ljbffr Thomson Reuters