AI Platform DevOps Engineer

STACK Infrastructure US; United States; On-site; USD 128,000 - 146,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Paid time off

Paid leave programs

Job summary

STACK Infrastructure’s DevOps Engineer, AI Platform, drives automation and reliable delivery pipelines for enterprise AI on Azure. You’ll own infrastructure‑as‑code, CI/CD, containerization, observability, and release automation enabling AI teams to ship RAG pipelines and integration services efficiently.

You will work at the intersection of cloud infrastructure, platform engineering, and MLOps, turning architecture into automated, governable, and cost‑efficient environments used across the

Qualifications

• Bachelor's degree in Computer Science, IT, Engineering, or related field, or equivalent.
• 5+ years of hands-on DevOps, SRE, or platform engineering with delivery track record.
• Strong Infrastructure as Code experience with Terraform, Bicep, or ARM.
• Proven CI/CD experience in Azure DevOps or GitHub Actions; containerization knowledge.

Responsibilities

• Automate infrastructure via IaC; manage Azure resources and AI platform components.
• Design, build, and operate CI/CD pipelines for code, infra, and AI deployments.
• Maintain environment parity across dev/test/prod; enforce governance and tagging standards.
• Operate AKS and Azure Container Apps; manage container images and registries.
• Support release workflows for agentic AI services and model endpoints.

Skills

DevOps

CI/CD

IaC

Azure

Python

Docker

AKS

Observability

Education

Bachelor's degree in Computer Science or related field

Tools

Terraform

Bicep

ARM

Azure DevOps

GitHub Actions

AKS

Azure Container Apps

Azure Monitor

Prometheus

Grafana

Job description

STACK Infrastructure’s DevOps Engineer, AI Platform, drives automation and reliable delivery pipelines for enterprise AI on Azure. You’ll own infrastructure‑as‑code, CI/CD, containerization, observability, and release automation enabling AI teams to ship RAG pipelines and integration services efficiently.

You will work at the intersection of cloud infrastructure, platform engineering, and MLOps, turning architecture into automated, governable, and cost‑efficient environments used across the