We are looking for a hands-on engineering manager to lead the team building LeanData's AI Products: the AI and agent capabilities that power go-to-market for the world's fastest-growing companies.
You own the technical vision for our AI and agent platform, drive 0-to-1 from ambiguous go-to-market problems to production-ready features, and set the evaluation discipline and AI best practices the whole engineering team follows. You manage and grow a small, strong team of AI/ML and agent engineers, and stay technical enough to design and ship alongside them. This is a strategic, opinionated, and fast-moving role.
This role reports to the SVP of Engineering and is based in our Santa Clara, CA office. You are required to be in office Mondays and Wednesdays each week.
What you'll be doing- Lead and grow the AI Products team: hire, coach, mentor, and raise the technical bar
- Set our AI and agent best practices, and the evaluation and quality bar for non-deterministic AI and LLM systems, across the whole engineering team
- Own the technical vision for our AI and agent platform, and build the evaluation infrastructure and abstractions other LeanData teams use to ship AI features
- Stay hands-on: design, review, and ship alongside your engineers (roughly half your time)
- Drive 0-to-1: turn ambiguous go-to-market problems into production-ready AI features, partnering with product, design, and data to shape the roadmap
- Own the quality, reliability, and delivery of the team's AI work, and drive the model and LLM upgrade pipeline, balancing quality, latency, and cost
Requirements- 4+ years building and shipping ML or AI/LLM systems in production, including 3+ years managing or leading engineers
- A track record of building and scaling AI-powered product capabilities 0-to-1, and of growing a small, strong engineering team while staying hands-on
- Strategic and opinionated: you turn ambiguous ideas into production-ready features and can defend sharp technical calls to product and engineering leadership
- Depth in evaluation and quality measurement for non-deterministic AI/LLM systems, including model selection and the tradeoffs between quality, latency, and cost
- Strong, current Python; you still write and review production code
- Applied AI experience is essential, including building products on large language models and partnering with product, design, and data to shape an AI roadmap
Bonus points if you have- Built on or near Salesforce, data warehouses, or against another large, messy enterprise data source
- Experience with the modern eval/observability stack (Promptfoo, Braintrust, Langfuse) and durable execution (Inngest, Temporal)
- A founder, founding-engineer, or early-engineer background owning a product end to end
CompensationThe salary for this role will be between $250,000 and $300,000 base, plus equity.
