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AI that actually understands healthcare is transforming operations, one workflow at a time.
The Role
Own the Context AI platform, including the healthcare context graph, customer-specific terminology and policy extensions, provenance, freshness, APIs, SDKs, and MCP access. Lead payer and PBM customer discovery, roadmap prioritization, pilots, product requirements, data-quality evaluations, developer experience, adoption, and go-to-market support. Partner closely with engineering, customers, sales, and marketing to drive production adoption and convert pilots into paid deployments.
Summary Generated by Built In
About Autonomize AI
Role Overview
Key Responsibilities
Customer Discovery
Context AI Product
Platform and Developer Experience
Execution
Go-To-Market
What Success Looks Like After One Year
Qualifications
Experience
AI and Technical Depth
The Right Mindset
What We Offer
Location
How To Apply
Autonomize AI is the healthcare industry's purpose-built AI platform for automating the complex administrative processes that consume clinicians, payers, and care teams: prior authorization, utilization management, care management, and claims processing. Backed by Valtruis, Cigna Group Ventures, Asset Management Ventures and top-tier VCs, we serve 3 of the top 5 U.S. health enterprises and are scaling aggressively.
We are not building another AI point solution. We are building the operating system for healthcare administration, a platform of AI agents, clinical workflows, and data fabric that replaces manual processes end to end. Context AI is the intelligence layer of that platform: one governed understanding of healthcare reference data and each customer's own policies, with the source behind every answer, that any agent or model can call.
This is a hands-on product role reporting to the VP of Product. You own Context AI: the Healthcare Context Graph, the enterprise extensions customers use to layer in their own terminology, policies, formularies and fee schedules, provenance and freshness, and the APIs, SDKs and MCP access that agents and developers build on. You also own customer discovery for the platform.
You are not a backlog manager. You spend real time with health plan and PBM data, analytics and AI teams, you find the decisions where shared context saves them time and money, and you turn that into a product engineers want to build and customers pay for.
- Run a weekly discovery rhythm with payer and PBM data, analytics, architecture and AI leaders
- Find the costly decisions where teams each keep their own rules, mappings and retrieval, and rank the opportunities by customer and business value
- Bring field signal from Sales, pre-sales and forward deployed engineers into the roadmap every week
- Own the Context AI roadmap: graph coverage across codes, crosswalks, coverage policy, payment rules and drug data, plus ontology editing, approvals, change history and source connections
- Run customer pilots with success criteria set up front, and turn what works into product
- Decide what we build next and what we stop doing
- Define what our engineers, partners and customer builders need to build agents and apps on the platform: APIs, SDKs, MCP access, docs and onboarding
- Measure adoption and remove the friction that slows builders down
- Write clear PRDs, acceptance criteria and evals for data quality, retrieval accuracy and freshness
- Set the release rhythm with engineering and hold it
- Give Sales and Marketing the positioning, packaging inputs and proof points for Context AI
- Join technical customer conversations when a deal needs a product voice
- Production adoption. Context AI running in production at multiple customers beyond pilot, on their own policies and terminology.
- Pilot conversion. Pilots that convert to paid, each with written success criteria.
- Platform pull. A growing number of our agents and customer-built agents calling Context AI by default.
- Discovery system. Every roadmap item traceable to a customer problem.
- Trusted data. Published accuracy and freshness metrics, with provenance on every answer.
- 5+ years in product management, with B2B data, AI or platform products shipped to enterprise customers
- A track record of customer discovery that changed what a team built
- Experience shipping APIs, SDKs or developer platforms that other teams build on
- Healthcare payer or PBM experience strongly preferred, especially with reference data such as code sets, coverage policy, formularies or fee schedules
- Working knowledge of knowledge graphs, ontologies, semantic layers, retrieval and how LLM agents use context
- Familiarity with MCP, REST APIs and data catalogs, and comfort writing SQL
- Familiarity with healthcare code sets and data standards such as ICD-10, CPT/HCPCS, NDC, FHIR and X12
- Driver, not a passenger. You pick up the problem and lead, without waiting to be asked.
- Embraces the mess. There is work in progress everywhere and less process than you would like. You move us from chaos to structure without slowing us down.
- Customer curiosity. You go to the customer first and come back with problems, not feature requests.
- Bias for action. Ships, measures and iterates. Makes decisions with imperfect information and owns the outcome.
- Simplifies and drives clarity. You make complicated infrastructure legible to a payer executive and an engineer alike.
- Honesty and humility. Transparent, low-ego, customer-leaned, truth-seeking.
- Competitive compensation and meaningful equity
- 100% employer-paid medical, dental, and vision insurance, plus 401(k), disability insurance, and employee assistance programs
- Direct work with experienced founders, engineering leaders and the largest health enterprises in the U.S.
- High ownership in one of the most consequential chapters of healthcare AI
In person in Austin, TX.
Send your resume and a brief note to [email protected] telling us about a customer insight that changed what you built.
Skills Required
- 5+ years of product management experience
- Experience shipping B2B data, AI, or platform products to enterprise customers
- Track record of customer discovery that changed what a team built
- Experience shipping APIs, SDKs, or developer platforms used by other teams
- Healthcare payer or PBM experience, especially with reference data such as code sets, coverage policy, formularies, or fee schedules
- Working knowledge of knowledge graphs, ontologies, semantic layers, retrieval, and LLM agent context
- Familiarity with MCP, REST APIs, and data catalogs
- Comfort writing SQL
- Familiarity with healthcare code sets and data standards including ICD-10, CPT/HCPCS, NDC, FHIR, and X12
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The Company
What We Do
Autonomize AI Agents & Copilots organize, contextualize and summarize unstructured data to reduce the administrative burden for healthcare knowledge workers to make data-driven decisions and improve patient outcomes. Our customers include health plans, providers and life sciences companies. Unlike generic AI systems retrofitted for healthcare, Autonomize deeply understands medical contexts, terminologies, and operational nuances. Our healthcare-focused AI Agents & Copilots augment knowledge work, drastically reducing administrative burden. Care management teams spend 78% less time per case, achieving an impressive 85% boost in case review efficiency. Prior authorization processes that traditionally take 20-30 minutes shrink to mere seconds, accompanied by an 80% reduction in manual errors, saving millions of dollars annually. Our AI Agents turn chaotic, unstructured healthcare data—clinical notes, PDFs, faxes, and claims—into structured, contextual information that informs decisions and actions. This has driven substantial real-world impact: organizations using Autonomize experience a 92% reduction in manual effort for care gaps and HEDIS chart reviews, dramatically improving compliance and STAR ratings. Autonomize AI is purpose-built for healthcare, transforming healthcare operations one workflow at a time through AI-native solutions that deliver immediate, scalable impact.
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