Lead Software Engineer AI (Staff Engineer)

You will be a Lead Software Engineer AI (Staff Engineer) responsible for the architecture and system design of Audit Suite.

• Shape the team's AI and patterns: Define patterns for building MCP servers, designing agents, novel uses of LLMs, experimentation, and scalable infrastructure. Your decisions will influence your product area and adjacent teams, not just a single feature.

• Work at real production scale: Build and evolve systems that operate over millions of documents, highly structured tax data, ever-changing laws, 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.

• Great fit for people who enjoy and thrive at setting technical direction, mentoring senior engineers, and spending most of their time in the code and architecture of AI systems.

• Shape the platform integration strategy across new and existing Thomson Reuters audit systems to provide world-class content and solutions for our customers.

Technical leadership and cross‑functional influence

• Lead multi‑quarter initiatives that cut across AI, product, and infra (e.g., a new orchestration layer, a low-latency retrieval system, or a unified knowledge base).

• Mentor senior and mid-level engineers, raising the bar on system design, code quality, and AI integration practices across the org.

• Be a go-to expert in new model capabilities, 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 testing, rollout, and postmortems.

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, multi‑step workflows, safety and guardrails, and robust error handling around third‑party LLMs (OpenAI, Anthropic, and others).

Scale, reliability, 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 and accounting use cases.

• Establish and refine SLOs, observability, and incident response for AI systems that must be correct, auditable, and trustworthy in professional workflows.

You are a fit for the position of Lead Software Engineer AI (Staff Engineer) if your background includes:

Required Experience & Skills:

• Bachelor's degree in Computer Science, Computer Engineering, a related field, or equivalent experience

• Proven track record of shipping production-grade AI systems to customers, including deployment, monitoring, evaluation, scaling, and ongoing operational ownership in enterprise environments.

• Overall 10+ years cumulative experience with 2 years in a lead role and minimum 5+ years full-stack development, building scalable cloud-based applications, web services, APIs and AI-driven products.

• C#/.NET expertise is

Alongside 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 acceptable).

• Experience architecting and implementing accessible front-end solutions, including: JavaScript, Typescript, HTML, CSS; experience with modern JavaScript frameworks, e.g., Angular, React, etc.

• Strong background in distributed systems: data modeling, API contracts, observability, resilience patterns, and performance tuning under load.

• Excellent communication skills and the ability to partner with product, design, and ML teams in a fast‑moving environment.

• Demonstrated interest in AI systems and new engineering paradigms: LLMs, agents, retrieval, or similar - you care about what "AI‑native" software should look like.

Preferred Skills & Experience

• Experience designing and implementing CI/CD pipelines (i.e., 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.

• Opinions and experience around automated testing, reliability, and release practices for systems with non-deterministic 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.

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