LeanData is the leader in enterprise Revenue Ops solutions, delivering a more holistic and unified go-to-market approach to business-to-business (B2B) enterprises seeking to accelerate growth. Backed by Correlation Ventures.
About the role
• Read the traces. Build intuition for how the agent behaves on live work, not on your test cases • At least one agentic product you took to launch. Not a prototype, not an internal pilot, not a feature with an LLM call in it. Something that ran in production and taught you things you’d do differently
What they're looking for
- • 7-8+ years in product management, owning products end to end
- • At least one agentic product you took to launch. Not a prototype, not an internal pilot, not a feature with an LLM call in it. Something that ran in production and taught you things you’d do differently
- • You wrote evals yourself. You’ve built the suites, set the pass criteria, and debugged failures by reading traces. You know how far apart eval theory and eval practice are
- • Depth to reason about tool calls, context, retrieval, latency, and cost as product decisions, and to hold your own with senior engineers
- • Real UX judgment. Opinions about interfaces you can show the work behind and defend past the first objection
- • Comfort without scaffolding. There’s no eval harness, research cadence, or instrumentation waiting for you. You build what you need and move
More about this role
• Set direction and make the calls on what ships, in what order, and what gets cut
• Take ambiguous problems and resolve product, system behavior, and interaction model together, not sequentially
• Build the prototypes and working examples that make an abstract idea arguable
• Work directly and often with RevOps and marketing ops leaders, in their environments, so as to bring the reality of their challenges into solutions
• Drive design partner interactions to iterate the product
• Define the correct behavior for the agents on this product
• Build the golden sets and help write meaningful evals yourself
• Read the traces. Build intuition for how the agent behaves on live work, not on your test cases
• When it goes wrong, characterize the failure: prompt problem, tool problem, context problem, or product problem
• Design the permissions and approvals that define what the agent does on its own and what it must ask about
• Design the recovery paths: a failed tool call, wrong data, an uncertain agent
• Design the audit trail, so a RevOps leader can prove next quarter what the agent did and why
• Navigate operating alongside Salesforce and other data systems, where the records live and...
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