About the job
At Protege, we aim to address one of the most significant challenges in AI—ensuring access to the right training data. The current process is often laborious, costly, and frequently leads to unsuccessful outcomes. Our platform streamlines the secure, efficient, and privacy-conscious exchange of AI training data.
Tackling the data issue in AI presents a monumental opportunity for growth. With support from top-tier investors, we are already collaborating with some of the most pioneering teams in the AI sector. The organization that excels in this domain is set to be one of the largest players in both AI and technology.
Our team is agile, trust-driven, and highly focused on speed and impact. We cultivate a culture that values adaptability, accountability, and a desire to influence the future of data and AI.
Role Overview
In this role, you will be responsible for overseeing how customers access, assess, and receive data—from samples and evaluation datasets to full contractual deliveries. You will define the product interfaces and processes for data transfer, ensuring that delivery is secure, repeatable, compliant with rights, and increasingly scalable. As we transition from custom deliveries to a product-centric platform, you will guide the evolution towards self-service access.
Your Key Responsibilities
Define Delivery as a Product Capability
Oversee delivery interfaces: full contractual deliveries, sample/evaluation datasets, secure file transfers, controlled access environments, and API-driven delivery pathways as necessary.
Clarify what “delivery” means within the product (beyond a mere operational transition).
Uphold Privacy & Rights at Access Points
Collaborate with the Privacy, Rights & Trust PM to integrate eligibility checks and usage restrictions into delivery workflows.
Ensure that access methods enforce policies (without being responsible for policy formulation).
Minimize Custom Delivery Work
Identify recurring challenges highlighted by Solutions Architecture and standardize packaging, formatting, and transformation patterns.
Transition delivery from manual, case-by-case construction to configuration-driven workflows.
Design the Self-Service Pathway
Determine which elements can be self-serviced, for which customer segments, under what constraints, and with what governance measures.

