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Salary
≈ $186k – $345k per year (Estimated)
Location
In office (San Francisco)
Seniority
Staff
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H-1B filings in 12 months: 1
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Oct 22, 2026.

Overview
Company
Impact
Profile match
0 Our story Health systems don't need another decision-support tool Midstream reveals hidden opportunities and empowers teams to act while they still matter.

Midstream is an AI-native financial operating system for health systems, founded by experienced entrepreneurs and backed by top-tier investors. We give finance, supply chain, and managed care teams real-time visibility into where margin is at risk, with a precise action plan for capturing it before it's gone.

Purpose-built for healthcare's complexity, Midstream transforms structured, unstructured, and external data into instant, contract-aware insights that drive smarter decisions. Our AI agents unify spend and revenue operations across the full back-office, learning and adapting with every interaction and delivering always-on intelligence that no point solution or one-off engagement can match.

We're compressing months to minutes and turning post-period hindsight into in-the-moment foresight. The tempo of healthcare finance is changing, and Midstream is leading it.

Opportunity

We're looking for a Product Manager to shape the foundational platform powering Midstream's AI-native products across supply chain, managed care, and pharmacy.

You'll own the strategy and roadmap for the data infrastructure, core AI agents, and shared capabilities that turn complex, fragmented healthcare data into trusted, actionable intelligence. Working closely with Engineering, Research, and Product, you'll make critical decisions about what we build, how we build it, and how we create a foundation that scales across customers and use cases.

As our first Platform PM, you'll have the opportunity to define how AI and data come together to solve some of healthcare's most complex financial challenges, enabling our teams to move faster and deliver meaningful impact to health systems.

How you'll make an impact

  • Own our platform strategy and roadmap: Define the vision, priorities, and roadmap for Midstream's shared platform. Make thoughtful decisions about which capabilities belong in the platform, what should initially be built within individual product domains, and how to balance speed of delivery with long-term scalability.

  • Build a trusted, connected data foundation: Partner with Engineering to shape how complex healthcare data is ingested, reconciled, modeled, and connected across products, contracts, vendors, facilities, and spend. Drive capabilities such as LLM-powered contract extraction, product categorization, and entity resolution, ensuring insights are accurate, explainable, and traceable to their source.

  • Advance our AI and agentic capabilities: Own the shared infrastructure and capabilities that power Midstream's AI agents. Work closely with Engineering and Research to establish how agents are built, evaluated, and improved, enabling product teams to develop reliable AI-powered experiences across multiple healthcare domains.

  • Make data quality a competitive advantage: Define standards, metrics, and continuous monitoring for data quality across the platform. Ensure accuracy, reliability, and transparency are built into our systems from the start, giving health systems confidence in the insights and recommendations they use to make financial decisions.

  • Enable product teams to move faster: Partner closely with Product Managers across supply chain, managed care, and pharmacy to understand their needs and build reusable capabilities that accelerate development. Continuously improve how we onboard new health systems and data sources, reducing complexity and increasing the speed at which we deliver value.

  • Build for enterprise scale and trust: Shape platform capabilities that meet the security, privacy, compliance, and reliability expectations of large health systems. Work with Engineering to make pragmatic architectural tradeoffs, evolving early solutions into robust, scalable infrastructure as the business grows.

Who you are

  • An experienced product leader: You have 8+ years of product management experience, including building enterprise analytics, data, or intelligence platforms that support multiple products or business domains.

  • Technically fluent: You have a strong understanding of data architecture, including ingestion, data modeling, entity resolution, APIs, and multi-tenant systems. You can engage deeply with engineers on technical decisions and tradeoffs.

  • AI-native: You have hands-on experience building AI-powered products and understand the opportunities, limitations, and evaluation challenges of LLMs and agentic systems.

  • Focused on data quality and trust: You understand the importance of accuracy, explainability, and traceability in enterprise platforms and have experience building products where data integrity, security, privacy, and compliance are essential.

  • A strategic, first- principles thinker: You have strong opinions, grounded in experience, about what belongs in a shared platform versus individual products. You can balance long-term architecture with the immediate needs of the business.

  • A pragmatic builder: You thrive in environments where the product is still taking shape. You know how to ship incrementally, learn from real-world usage, and evolve early capabilities into scalable, reliable solutions.

  • A strong cross-functional partner: You communicate clearly, document decisions thoughtfully, and build alignment across Product, Engineering, and Research while navigating complex technical and business tradeoffs.

  • Excited by healthcare's complexity: You're motivated by the opportunity to apply AI and modern data technology to meaningful healthcare challenges. Experience with healthcare data, including EHR, ERP, supply chain, pharmacy, or payer data, is a plus.

  • Experienced with complex data ecosystems: Familiarity with knowledge graphs, ontologies, data catalogs, or master data management is a plus, as is experience building products at an early-stage company.

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