Qualifications
Responsibilities
Benefits
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.
What you'll do:
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.
About You:
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
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 expertiseand experience withproduction systemsusing frameworks like ASP.NET Core (or similar), relational databases (SQLServer, PostgreSQL or equivalent), and amajor cloud provider(AWS preferred, Azure).
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.
Proven track record leading large, complex projects end0to0end: architecture, execution, rollout, and long0term operation.
Excellent communication skills and the ability to partner with product, design, and ML teams in a fast0moving environment.
Demonstrated interest in AI systems and new engineering paradigms: LLMs, agents, retrieval, or similar 6 you care about what AI0native software should look like.
Preferred Skills & Experience
Experience designing and implementing CI/CD pipelines (i.e., GitHub Actions)
Hands0on experience integrating LLM APIs (e.g., OpenAI, Anthropic) into production applications, including prompt/response management, cost controls, and safety considerations.
Experience with AI0adjacent 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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