Senior Platform Engineer

📋 Job Overview

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.

🏢 About Interra Health

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.

🎯 The Role

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.

✅ Key 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 and infrastructure deployment workflows from the ground up.
• Own observability and reliability for AI and platform services, applying SRE principles such as SLOs, incident response, and blameless postmortems.
• Partner with the Lead AI Platform Engineer to implement the AI platform roadmap, building the reusable patterns, guardrails, and “paved road” solutions other engineering teams adopt.
• Evaluate, pilot, and support adoption of AI coding assistants and platform tooling across the engineering AI landscape, including GitHub Copilot, M365 Copilot, and other emerging AI dev tools, with a build-versus-buy mindset balancing speed, cost, security, and long-term maintainability.
• Participate in Agile ceremonies, track and prioritize work in Jira, and influence release planning and architectural decisions.
• Participate in on-call rotations and provide Level 3 support for production platform and AI systems.
• Contribute to internal documentation, runbooks, and knowledge-sharing so AI and platform practices scale beyond any one person.

📌 Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience, plus 6+ years of hands-on experience in DevOps, Cloud Engineering, or Site Reliability Engineering.
• Deep expertise in Microsoft Azure, including infrastructure as code, networking, identity/access, DNS, and load balancing.
• Practical, hands-on experience applying AI, GenAI, or automation tooling to engineering workflows, developer productivity, or production systems, such as LLMOps/GenAIOps, model gateways, RAG patterns, agent frameworks, or AI observability.
• Advanced proficiency with Terraform, containerization and orchestration (Docker, Kubernetes), and CI/CD platforms such as GitHub Actions.
• Proficient in scripting or programming languages (e.g., Python, PowerShell).
• Hands-on comfort with Jira and Agile workflows.

⭐ Desirable Experience

• Experience with AI coding assistants and platform tooling, including GitHub Copilot, M365 Copilot, and other emerging AI dev tools.

🎁 Benefits

The total compensation range includes the budgeted base and bonus for the role. The final offer will be based on the candidate's interview performance, skills and experience against the role they are being considered for. Compensation: $130K – $170K

🛂 Visa & Eligibility

No visa or eligibility information provided.