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Open nowPosted 20 hours ago

Product Manager, AI Platform (Context AI) - Austin based

Autonomize22 open roles

Where
Austin
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Your applicationOpen nowProduct Manager, AI Platform (Context AI) - Austin basedAutonomize · Austin

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The clock on this job

Early applications get read.

13.9% of postings close within 7 days. Measured by our own scanner across the market. Autonomize postings stay open a median of 19 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.9%7 days
  4. 22.4%14 days
  5. 38.1%30 days
  6. 59.0%60 days
This job: posted 20 hours ago

Autonomize median: 19 days open

The posting

About Autonomize AI

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.

Role Overview

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.

Key Responsibilities

Customer Discovery

  • 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

Context AI Product

  • 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

Platform and Developer Experience

  • 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

Execution

  • Write clear PRDs, acceptance criteria and evals for data quality, retrieval accuracy and freshness
  • Set the release rhythm with engineering and hold it

Go-To-Market

  • 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

What Success Looks Like After One Year

  • 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.

Qualifications

Experience

  • 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

AI and Technical Depth

  • 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

The Right Mindset

  • 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.

What We Offer

  • 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

Location

In person in Austin, TX.

How To Apply

Send your resume and a brief note to [email protected] telling us about a customer insight that changed what you built.

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