Senior AI Platform Engineer - Azure, DevOps & GenAI

Interra Health; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Interra Health is scaling AI across engineering, building secure Azure infrastructure and AI-enabled platform services. This hands-on role owns MCP server configuration, LLMOps tooling, and cloud security, while partnering with engineers on CI/CD and observability.

You will drive automation, reliability, and scalable deployment practices in a post-merger environment, shaping the AI platform roadmap and governance.

Qualifications

• Bachelor's degree and 6+ years hands-on DevOps/Cloud Engineering.
• Deep expertise in Microsoft Azure, including IaC, networking, identity/access, DNS, and load balancing.
• Practical experience applying AI/GenAI tooling to engineering workflows.
• Advanced proficiency with Terraform, Docker, Kubernetes, and CI/CD tools.
• Scripting in Python or PowerShell; secure engineering practices.

Responsibilities

• Design, build, and operate secure, scalable Azure infrastructure underpinning core platform and AI workloads.
• Configure MCP servers and AI integration points for enterprise use.
• Build and operationalize AI-enabled capabilities and observability, including SRE practices.
• Implement and improve CI/CD pipelines with GitHub Actions and DevSecOps.
• Own observability and reliability with SLOs and incident response.
• Collaborate to implement AI platform roadmap and guardrails.
• Pilot and support adoption of AI coding assistants across engineering.
• Participate in Agile ceremonies and on-call rotations.
• Contribute to internal docs and runbooks.

Skills

Azure cloud engineering

DevOps practices

LLMOps / GenAIOps

Terraform

Docker / Kubernetes

CI/CD (GitHub Actions)

SRE / observability

Python / scripting

Security & compliance

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Terraform

GitHub Actions

Docker

Kubernetes

Azure

Jira

Job description

Interra Health is scaling AI across engineering, building secure Azure infrastructure and AI-enabled platform services. This hands-on role owns MCP server configuration, LLMOps tooling, and cloud security, while partnering with engineers on CI/CD and observability.

You will drive automation, reliability, and scalable deployment practices in a post-merger environment, shaping the AI platform roadmap and governance.