Description
Thomson Reuters products power professionals shaping the world across legal, tax, accounting, and audit. As a Lead Software Engineer AI (Staff Engineer AI) on Cloud Audit Suite, you will own backend and AI orchestration systems that transform frontier models into reliable, production-grade workflows at scale.
About the Role
- As a Lead Software Engineer AI (Staff Engineer), you will be responsible for the architecture and technical direction of Audit Suite.
- Define AI engineering patterns for MCP servers, agent frameworks, LLM integration, experimentation, and scalable infrastructure.
- Build systems operating across millions of documents, structured financial data, evolving regulations, and thousands of concurrent AI interactions.
- Lead across engineering, product, UX, and AI teams to rapidly design and deliver customer-facing solutions.
- Set technical direction, mentor senior engineers, and stay hands-on in architecture and code.
- Drive platform integration strategy across Thomson Reuters audit systems.
Technical Leadership & Cross-Functional Influence
- Lead strategic initiatives spanning AI, platform, and infrastructure.
- Mentor engineers and elevate system design, code quality, and AI engineering practices.
- Partner with AI/ML teams, researchers, designers, and product managers to convert emerging AI capabilities into trusted customer solutions.
- Influence roadmap, technical strategy, experimentation, testing, rollout practices, and operational excellence.
Design & Own AI-First Backend Systems
- Architect and build backend services using C#/.NET, Python, FastAPI, PostgreSQL, AWS, and Vercel that power AI-driven workflows and document-centric experiences.
- Develop AI orchestration capabilities including MCP servers, tool calling, workflow routing, guardrails, reliability, and LLM integrations.
- Design high-throughput, low-latency AI systems using caching, queuing, rate limiting, failover, and cost optimization strategies.
- Build retrieval and search systems leveraging large document collections, vector databases, and indexing technologies.
- Establish observability, SLOs, and incident management practices for auditable and trustworthy AI systems.
About You
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience.
- 7+ years of software engineering experience, including 2+ years in technical leadership roles and 3+ years building scalable cloud applications, APIs, and AI-enabled products.
- Proven track record of shipping production-grade AI systems to customers, including deployment, monitoring, evaluation, scaling, and ongoing operational ownership in enterprise environments.
- Full Stack experience with Python, JavaScript, TypeScript, and modern frameworks such as React or Angular.
- Strong distributed systems expertise, including APIs, data modeling, observability, resiliency, and performance optimization.
- Proven success leading complex projects from architecture through long-term operation.
- Deep interest in AI-native software, including LLMs, agents, retrieval, and modern AI development patterns.
Benefits
- Hybrid Work Model: flexible hybrid working environment
- Flexibility & Work-Life Balance: supportive workplace policies
- Career Development and Growth: continuous learning and skill development
- Industry Competitive Benefits: comprehensive benefit plans
- Culture: award-winning reputation for inclusion and belonging, flexibility, work-life balance
- Social Impact: opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives