Job description

Location: San Francisco, CA Work Model: Onsite (occasional travel to customers) Industry: Data infrastructure / AI Compensation: $200K-$350K base, with flexibility above that band for an exceptional profile About the Company Our partner operates a canonical identity graph for people and companies worldwide, delivered as both an index and an API. Rather than indexing the web on keywords, they parse and resolve the entities on every page, verify source authority, and deduplicate, producing a pre-verified grounding layer that AI agents can act on instead of retrieving on the fly. The company recently crossed $10M in ARR and counts a mix of high-growth platforms, a global consultancy, and large technology companies among its customers. The Opportunity This is a founding product manager seat and the second product hire at the company. It is an individual-contributor role with unusually wide surface area: the product team decides which derived datasets get built from an enormous already-indexed corpus, and how a self-serve business scales to match a sales-led one. The work splits across two verticals. On the data side, you will identify the derived datasets the machine-learning team should build next, prioritize them against customer demand, and make sure they land as products people actually use. On the product-led growth side, you will scale self-serve toward the run rate of the sales-led business, enabling users to build their own internal workflows and agents on top of the data. The role exists because features have shipped without product ownership and gone unused; you are the person who closes that loop. Responsibilities • Identify what customers are asking for and judge whether the current product already solves it • Define and prioritize derived data products (for example technographics or fraud signals) with the machine-learning team • Own the roadmap end to end: requirements, implementation, launch, adoption, and the feedback loop after launch • Scale the product-led growth motion toward parity with the sales-led business • Work directly with customers building agents and internal workflows on top of the platform • Make sure shipped features get into customers' hands and keep improving rather than going dormant Requirements • 4-5+ years of product management experience, operating as an individual contributor • Computer science degree, with the technical depth to reason about agent-facing and ML-derived products • Startup experience and comfort in a zero-to-one environment • Track record of owning a product area end to end and growing it measurably • Analytical, scrappy, and able to move without a large supporting org • Experience with data products, ML-driven features, or product-led growth motions is strongly preferred

Requirements

Must-haves

Location: San Francisco, CA
Work Model: Onsite (occasional travel to customers)
Industry: Data infrastructure / AI
Compensation: $200K-$350K base, with flexibility above that band for an exceptional profile
Identify what customers are asking for and judge whether the current product already solves it
Define and prioritize derived data products (for example technographics or fraud signals) with the machine-learning team
Own the roadmap end to end: requirements, implementation, launch, adoption, and the feedback loop after launch
Scale the product-led growth motion toward parity with the sales-led business
Work directly with customers building agents and internal workflows on top of the platform
Make sure shipped features get into customers' hands and keep improving rather than going dormant
4-5+ years of product management experience, operating as an individual contributor
Computer science degree, with the technical depth to reason about agent-facing and ML-derived products
Startup experience and comfort in a zero-to-one environment
Track record of owning a product area end to end and growing it measurably
Analytical, scrappy, and able to move without a large supporting org

Nice-to-haves

Experience with data products, ML-driven features, or product-led growth motions is strongly preferred

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiapiml

Platform: workable
Effort: medium