Product Manager, Data Access - Remote
14 hours ago
Job description
Company Overview:
We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data.
Solving AI's data problem is a generational opportunity. We're backed by world-class investors and already powering partnerships with some of the most ambitious teams in AI. The company that succeeds will be one of the largest in AI — and in tech.
We're a lean, fast-moving, high-trust team of builders who are obsessed with velocity and impact. Our culture is built for people who thrive on ambiguity, own outcomes, and want to shape the future of data and AI.
Role Overview
You will own how customers access, evaluate, and receive data—from samples and evaluation sets to full contractual deliveries. You'll define the product surfaces and mechanisms through which data leaves the platform, ensuring delivery is secure, repeatable, rights-compliant, and increasingly scalable. As Protege shifts from bespoke delivery to a product-led platform, you'll shape the path toward staged self-service access.
What You Will Own
Define delivery as a product capability
Own delivery surfaces: full contractual deliveries, samples/evaluation datasets, secure file transfer or controlled access environments, and API/structured delivery pathways as appropriate.
Establish what "delivery" means in-product (not just an operational handoff).
Enforce privacy & rights at Point of Access
Partner with the Privacy, Rights & Trust PM to embed eligibility checks and usage constraints into delivery workflows.
Ensure access mechanisms enforce policy (without owning policy definition).
Reduce delivery bespoke work
Identify repeated friction surfaced by Solutions Architecture and standardize packaging, formatting, and transformation patterns.
Shift delivery from manual, deal-by-deal construction to configuration-driven workflows.
Design the path to self-service
Define what can be self-serve, for which customers, under what guardrails, and with what controls/visibility.
Start with constrained, high-confidence surfaces (e.g., samples) and expand intentionally.
Represent delivery state in the platform
Define delivery status models and ensure internal visibility into what was delivered, to whom, under what constraints.
Enable auditability and reproducibility.
Cross-Functional Alignment
You'll work closely with:
PM, Data Inventory & Partner Systems: ensure what's discoverable is deliverable
PM, Privacy, Rights & Trust: enforce eligibility and compliance at access time
GTM & Partnerships: improve sampling and evaluation velocity
Engineering: owns ingestion execution and infrastructure
Who You Are
PM experience in data platforms, marketplaces, APIs, or enterprise delivery systems
Experience building secure access workflows or permissioned systems
Strong product + execution instincts; comfortable with operational reality
Comfortable at the intersection of legal, engineering, and GTM
Ability to stage maturity over time rather than overdesign upfront
What Success Looks Like
Faster sample-to-deal conversion cycles
Reduced bespoke delivery engineering
Clear, repeatable delivery paths across deals
Fewer privacy/rights disputes at delivery time
Early, constrained self-service capabilities launched successfully
Strategic Impact
This role directly influences revenue velocity, customer trust, platform scalability, and Protege's long-term self-service posture—because data delivery is where platform value becomes real.
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