
Solutions Lead, Assessments
What you need
- Shaped and delivered complex customer engagements
- Coordinated cross-functional stakeholders without direct authority
- Managed changing requirements and difficult timelines
- Built playbook or process adopted by others
- Worked with healthcare data
What you'll do
- Translate customer goals into assessment scopes
- Coordinate engineering, commercial teams and data partners
- Serve as primary delivery contact to customers
- Assess technical feasibility and recommend scope options
- Build reusable playbooks for intake and acceptance
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.
Summary
You will shape and deliver healthcare AI assessments around the decisions customers need to make. Translate their needs into feasible scopes and own delivery across DataLab, engineering, verification and data partners, from initial feasibility through customer acceptance.
Combine solution design, hands-on delivery and strategic judgment. Weigh trade-offs across data sources, evaluation approaches and capacity; recommend priorities and reusable investments. Stay close to the technical work to challenge assumptions and troubleshoot dependencies, and turn delivery experience into playbooks and better operating decisions.
What You’ll Do
Translate customer goals into assessment scopes, success criteria and delivery plans with clear technical and commercial assumptions.
Coordinate DataLab, engineering, commercial teams and data partners through each delivery stage.
Coordinate partner specifications and data-readiness checks across relevant EHR, claims, imaging, pathology and text sources.
Serve as the primary delivery contact, making technical decisions, progress, risks and trade-offs clear to customers.
Assess technical feasibility and recommend scope, source or execution options based on customer value, effort, risk and capacity.
Coordinate data-quality, privacy, scientific and technical readiness reviews with the responsible experts before work advances.
Manage changing requirements and competing projects, recommending priorities and showing the impact on timing, effort and deliverables.
Build reusable playbooks for intake, feasibility, QA, partner handoffs, escalation and acceptance.
Use delivery evidence to prioritize process and tooling improvements, explaining expected customer value and capacity benefits.
Coordinate results delivery, customer acceptance and the handoff into the next assessment or rerun.
What Success Looks Like
First 30 days: Understand the customer decisions, healthcare data needs and technical dependencies across the assigned portfolio. Establish a delivery cadence, baseline effort and rework, and identify the most important constraints on delivery.
By 60 days: Lead assigned customer deliveries, move at least one through a meaningful milestone, and apply the playbook across two projects or delivery cycles. Secure agreement on a scope or prioritization recommendation that balances customer value, technical feasibility and capacity.
By 90 days: Lead a project to acceptance or its agreed checkpoint, demonstrate improvement against a delivery baseline, and make the playbook usable by another teammate. Recommend a prioritized delivery roadmap with concrete process or tooling investments and expected benefits.
What You Bring
You have shaped and delivered complex customer or partner engagements, translating an ambiguous need into a feasible solution and a concrete outcome.
You have coordinated technical, operational and external stakeholders, making dependencies and decision ownership clear without relying on direct authority.
You have managed changing requirements and difficult timelines while maintaining clear expectations and customer trust.
You have built a playbook or operating process that other people adopted, and can show how it reduced confusion, delay or repeated work.
Optional: You have worked with healthcare data before
Optional: Experience with AI evaluations, ML products or enterprise data delivery is valuable. SQL, Python and API tooling are helpful, not required; you must be able to interpret technical evidence and work effectively with the specialists who produce it.
Protege Values
Pass the Loved Ones’ Test
We act with integrity and do the right thing — especially when it’s hard and no one is watching.
Always Find a Way
We are resourceful, resilient builders who solve hard problems and push through obstacles.
Go Fast and Grow Fast
Velocity matters. We move with urgency, learn quickly, and continuously improve as individuals and as a company.
Practice Kindness and Candor
We communicate directly and respectfully, building trust through honest feedback and genuine care for one another.
Deliver Together
We win as one team. Collaboration, accountability, and shared ownership drive our success.
Own the Outcome. Hone the Craft.
We take pride in our work, sweat the details, and continuously raise the bar for excellence.
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About Protege
The biggest unmet need in AI today is getting access to the right training data. Data holders often don’t know where to start and are rightly concerned about governance, intellectual property, and security implications. AI companies can spend years finding and negotiating access to the data they need. Protege is solving these problems by providing an easy-to-use platform to connect data holders with vetted data users.
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