Principal AI Platform Engineer

Matter Health•Nashville, TN

22h•Remote

About The Position

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.

Requirements

Bachelor’s degree in Computer Science, Data Science, Engineering, or a related discipline, or equivalent practical experience.
10+ years of experience in software, platform, infrastructure, or related engineering roles.
3+ years operating at the Staff, Principal, or Architect level with responsibility for setting technical direction across teams or an organization.
2+ years personally designing, building, deploying, and operating production LLM or AI-agent systems.
Demonstrated ownership of an enterprise platform strategy and roadmap, including architecture, reusable tooling, deployment environments, and integration foundations.
Hands-on experience with AI agents, workflow automation, RAG or vector infrastructure, APIs, and enterprise integrations.
Experience with MCP or a comparable agent integration or context-sharing framework.
Experience designing governance, security, or model-risk controls for AI or other high-risk technology in a regulated environment.
Experience handling PHI, HIPAA-regulated data, or similarly sensitive and regulated information.
Experience establishing monitoring, observability, production reliability, incident response, root-cause review, and rollback or shutdown practices.
Direct ownership of technology budgets and vendor relationships, including usage-based cloud or model spend, vendor evaluation, and contract recommendations.
Strong written and verbal communication skills, with the ability to set standards and influence technical, clinical, operational, security, and executive stakeholders without direct authority.

Nice To Haves

Experience building technology platforms in healthcare or another highly regulated environment.
Experience with EHR, CRM, ticketing, telephony, data-warehouse, or RPA integrations.
Familiarity with NIST AI RMF, ONC HTI-1, CMS guidance, state AI requirements, or comparable regulatory frameworks.
Experience enabling distributed engineering or business teams through platform tooling, reusable components, and technical documentation.

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, contract recommendations, and platform investment decisions in partnership with the CTO.
Enable engineers, automation specialists, and business teams to build on the platform through clear documentation, reusable patterns, technical guidance, and hands-on problem solving.
Partner with technical, security, clinical, operational, data, product, and executive stakeholders to translate business needs into secure and scalable platform capabilities.
Measure platform adoption, reliability, business impact, and risk, and use those findings to guide roadmap priorities.