Principal AI Platform Engineer

Matter Health delivers primary and preventive healthcare directly to older adults living in public housing communities. Our mission is simple: to improve healthcare access by meeting patients where they are and building trusted relationships within the communities we serve. We are rapidly expanding and are seeking mission-driven professionals who thrive in fast-paced, people-centered environments. Total Healthcare. Where you live.

About the Role

Matter Health is seeking a Principal AI Platform Engineer to build and lead the technical foundation for our organization-wide AI capabilities. This is a senior, hands-on individual-contributor role with no direct reports. You will own the AI platform strategy, roadmap, architecture, governance, reliability, and budget while creating the environments, deployment pipelines, reusable components, connectors, and integration scaffolding that enable other teams to build and deploy AI agents and workflow automations safely. Success in this role requires balancing enablement with protection: helping teams move quickly while establishing the standards, controls, observability, and incident-response practices needed in a regulated healthcare environment. You will partner closely with the CTO, Software Engineering, Information Security and Compliance, and clinical and operational leaders. This is a fully remote role. Candidates located in Nashville or Memphis, Tennessee, are preferred. Occasional travel of up to 10% may be required for company meetings, team offsites, or business needs.

Responsibilities

• Own the strategy, roadmap, reference architecture, and day-to-day operation of Matter Health’s enterprise AI platform.
• Design and maintain development, testing, and production environments; deployment pipelines; reusable platform components; and secure integration patterns for AI agents and workflow automations.
• Build connectors and integration scaffolding across enterprise systems such as EHR, CRM, ticketing, telephony, and data-warehouse platforms.
• Evaluate and implement agent orchestration and runtime technologies, RAG and vector infrastructure, MCP or comparable integration and context-sharing frameworks, RPA, model APIs, and supporting tools.
• Establish and enforce AI engineering standards and governance practices, including identity and access controls, PHI and regulated-data safeguards, vendor-risk review, auditability, human oversight, and safe rollback or shutdown mechanisms.
• Define logging, monitoring, observability, reliability, and incident-response practices for production AI systems; lead root-cause reviews and continuous improvement after incidents.
• Own the AI platform budget and vendor relationships, including usage-based cloud and model spend, vendor evaluation,