Staff Software Engineer
Summary
Hands-on staff-level backend engineer building the platform behind AI products for tax, accounting, and audit professionals: LLM orchestration (agents, tool calling, MCP), retrieval across millions of documents, and production services in Python/FastAPI on AWS and PostgreSQL, plus mentoring and leading projects end to end.
Lead Software Engineer (Staff Level) | AI Products & Platform
I’m partnering with a global technology company investing heavily in AI products for tax, accounting, and audit professionals. This team is building tools that help professionals work through complex documents, find relevant evidence, and complete high-stakes client work with greater speed and confidence.
It’s a small, senior team with the pace and ownership of a startup, access to a large customer base, and the resources to build for real production scale. They’re looking for a hands-on Staff Engineer to shape the platform behind these products while continuing to write production code.
What you’ll own
- Design and build the backend services powering AI agents, conversations, workspaces, and document workflows
- Develop orchestration for LLMs, tool calling, MCP, and multi-step tasks
- Improve retrieval and knowledge systems operating across millions of documents
- Make practical decisions around latency, reliability, observability, scalability, and model cost
- Lead projects from technical design through launch and ongoing operation, while mentoring engineers and influencing direction across teams
Qualifications
- Recent experience designing, building, and shipping production products or platforms in a strong product, SaaS, or technology engineering organization
- Staff-level technical ownership: leading complex projects end to end while continuing to write production code
- Strong Python backend engineering experience, ideally with FastAPI, APIs or microservices, PostgreSQL, and AWS
- Experience designing distributed systems and operating them reliably at scale
- Hands-on experience integrating LLMs into products; experience with agents, tool calling, MCP, RAG, or retrieval is especially relevant
- Sound judgment around performance, observability, resilience, and cost in production
- Ability to mentor engineers, make clear technical tradeoffs, and influence engineering direction across teams
If you’re a hands-on Staff Engineer who wants to own a meaningful part of an AI product that professionals use in their day-to-day work, send me a message and I’ll share more details.