Senior Platform Engineer

About the role

Interra Health is a fast-growing healthcare technology company transforming how providers and patients navigate the prescription journey. Formed through the merger of DoseSpot, Arrive Health, and pVerify, Interra Health delivers trusted eligibility, real-time coverage and pricing insights, prescribing tools, and pharmacy transparency at the point of care—helping providers make informed decisions and patients access the right medications with greater clarity and affordability. Backed by strong market momentum and a bold vision for the future of connected care, Interra Health offers the chance to join an innovative, mission-driven team working at the intersection of software and healthcare to reduce friction, improve access, and make the healthcare experience better for everyone.

Interra Health is scaling AI across engineering: developer velocity, operational resilience, automation, observability, and secure delivery, and the Senior Platform Engineer is the hands-on builder who turns that ambition into working systems. Reporting to the Director, Platform & Operations, this role owns the design, implementation, and operation of AI-enabled platform capabilities: MCP server configuration and reliability, LLMOps/GenAIOps tooling, secure model integration patterns, and the underlying Azure cloud infrastructure those capabilities run on. This is an individual-contributor role, not a people-management seat. You will partner closely with the Lead AI Platform Engineer, who owns the AI enablement roadmap and team, and with the engineers who run the core Azure platform, but you carry direct, hands-on responsibility for building, hardening, and operating the AI layer itself, from infrastructure as code and CI/CD through to production monitoring, security, and compliance for AI workloads. The right person has deep DevOps and cloud engineering fundamentals paired with genuine, practical fluency in applying AI to real infrastructure and developer-experience problems, someone who’d rather ship a working integration than write another proposal about one.

Responsibilities

• Design, build, and operate secure, scalable, highly available Azure infrastructure underpinning both core platform services and AI workloads, using Infrastructure as Code (Terraform).
• Configure, secure, and operate MCP servers and related AI integration points, including access patterns, reliability, and lifecycle management, for enterprise use.
• Build and operationalize AI-enabled capabilities, including internal engineering assistants, workflow automation, infrastructure insights, and incident-response support, applying practical LLMOps/GenAIOps practices for evaluation, monitoring, logging, cost management, and access control.
• Implement and continuously improve CI/CD pipelines in GitHub Actions and DevSecOps practices, integrating security and compliance into AI