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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # VP, Data/AI Platform - **Company:** MatrixCare - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $245,000.0 - $275,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Business Software, Information Engineering, Data Governance, Data Infrastructure, Identity and Access Management, Machine Learning, Software Deployment, Data Streaming, Enterprise Data Management, Cloud Platform System, Data Classification, Fast Healthcare Interoperability Resources, Retrieval-Augmented Generation, Snowflake, Model Validation, Electronic Medical Records, Data Layers, AI Platforms, Kubernetes, Information Technology, AWS Data Analytics, Data Management, Machine Learning Operations - **Published:** October 7, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=a43bf641aca1acc2 ## About the Role * Bachelor's degree required. Advanced degree in a quantitative, computer science, or business discipline preferred. * 12 or more years of relevant experience across data platform, data engineering, data science, and machine learning, including 5 or more years leading leaders. * Demonstrated accountability for a data and artificial intelligence discipline's strategy, budget, and outcomes at the executive level, ideally within healthcare or another environment where the data carries regulatory weight. * Hands on fluency, not oversight alone, with a modern cloud data stack. Direct working experience with Snowflake and with AWS data and artificial intelligence services including Bedrock, SageMaker, and Redshift. * Demonstrated record of moving data science and machine learning work from idea into production quickly, with measurable business results attached rather than models that stopped at the prototype. * Experience building and operating on protected health information or equivalently regulated data, including data use agreements, data classification, de-identification, and access governance. * Experience owning a data platform architecture decision and the migration or modernization that followed it, including the operating model that ran it afterward. * Working knowledge of agentic artificial intelligence and large language model orchestration frameworks, retrieval augmented generation, model evaluation and responsible artificial intelligence guardrails, and human in the loop workflow design. * Experience leading globally distributed teams, including engineering capability in India. * Track record of partnering with product and commercial leaders to turn platform capability into revenue rather than into internal tooling. Preferred Qualifications: * Prior experience in healthcare technology, electronic health record platforms, or post-acute care across skilled nursing, home health, hospice, senior living, or private duty. * Familiarity with clinical assessment instruments and the reimbursement models built on them, and with the interoperability standards that move healthcare data, including FHIR and TEFCA participation. * Experience commercializing data, including de identified data products, benchmarking offerings, and the contractual and privacy work that makes them sellable. * Experience in a private equity backed or growth-oriented software business, including exposure to a board, audit committee, or sponsor. * Familiarity with software as a medical device consideration and the decision boundary documentation clinical models require. * Experience embedding artificial intelligence assisted delivery practices inside an engineering organization, with adoption and impact measured rather than assumed. * Experience with platform engineering and internal developer platform practices at enterprise scale. ## Description * Data Engineering * Artificial Intelligence * AWS * Snowflake * Strategy * Leadership * HealthTech, The VP, Data/AI Platform owns the enterprise data platform, the artificial intelligence and machine learning agenda, and the shared platform services every product team builds on. As Vice President, you set the strategy for how we turn our most valuable asset, data, into a competitive advantage leveraging AI. You lead a multidisciplinary organization spanning data engineering, data science and machine learning across the United States and India. You are accountable to the Chief Technology Officer and to the executive leadership team for the reliability and economics of the data platform, for moving artificial intelligence capability from idea into production at a pace the market rewards, and for the governance that makes all of it defensible to customers, auditors, and regulators., * Own the enterprise data and artificial intelligence strategy, and translate it into a funded, sequenced roadmap that the executive leadership team and the board can hold you to.Own the target architecture for the data platform, including the cloud data platform, streaming and batch ingestion, the semantic and consumption layers, and the reliability, quality, and cost posture of the whole estate. * Deliver data products that customers experience directly: benchmarking, operational and clinical insight, and the analytics that make the clinical and financial performance of a provider organization visible and actionable. * Own the artificial intelligence and machine learning portfolio end to end, from problem selection and model development through evaluation, human in the loop design, production deployment, monitoring, and the measured business outcome each capability is meant to produce. * Select and stand up the orchestration, tooling, and machine learning operations platform that agentic and generative capability runs on, and hold it to enterprise reliability and cost standards. * Establish and run artificial intelligence governance: model risk management, data classification, evaluation and guardrail standards, bias and drift monitoring, and the audit evidence that regulated customers expect before they will buy. * Own shared platform services and the internal developer platform, so product engineering teams ship faster on common capability rather than rebuilding it team by team. * Own data governance, master data and patient identity, and interoperability of the data layer, so that a patient, a facility, and an episode mean the same thing everywhere in the company. * Partner with the VP, Product Management and the commercial organization to convert platform capability into packaged, priced offerings, and to choose investment from customer and usage evidence rather than from opinion. * Own the build, buy, partner, or license decision for artificial intelligence capability, with the sizing, governance, and contractual analysis to support it. * Manage the domain budget and vendor portfolio, including cloud and data platform spend, with a clear view of unit economics and a bias toward capability that compounds rather than capability that is rented indefinitely. * Recruit, develop, and retain a high performing, diverse team across distributed locations. Conduct regular one to ones and performance conversations, build succession beneath every leadership seat, and grow the technical bench rather than concentrating expertise in a few people., * You translate data and artificial intelligence capability into customer value and commercial outcome rather than into capability slides * You make quality decisions without incomplete information, then revisit the decision as evidence arrives * You have built organizational design, workforce planning, and budget ownership at scale * You have successfully built and mentored your teams across time zones and cultures, and grow successors rather than dependencies * You govern vendors and delivery partners without ceding technical direction to them * You balance speed to market against governance, privacy, and clinical safety, and can explain that balance to a customer, an auditor, and a board * You are a trusted advisor to the Chief Technology Officer, the executive leadership team, and the board