DevOps Engineer – AI/ML Platform (CI/CD + Terraform + Azure/AWS)

Job Description

DevOps Engineer supporting a high-impact multi-workstream AI program focused entirely on enabling rapid, reliable, and secure delivery of AI/ML applications and services. 100% dedicated to AI initiatives, spanning early experimentation through full productionization. Top 3 required skills: CI/CD Tooling; Infrastructure as Code (Terraform, primary); Cloud Platforms (Azure & AWS).

Requirements

• • 3–5+ years of experience in DevOps or Platform Engineering, including production support
• • Strong experience with Windows Server administration and troubleshooting; Linux experience is a plus
• • Hands-on expertise with CI/CD tooling: Azure DevOps, GitHub Actions, and Ansible
• • Solid experience with cloud platforms (Azure and AWS), including networking, identity, and storage
• • Deep proficiency with Infrastructure as Code; Terraform as primary tooling (required)
• • Strong scripting and automation skills (PowerShell required; Python a plus)
• • Hands-on experience with Docker and Kubernetes (deployments, scaling, upgrades, operational hardening)
• • Experience implementing monitoring, observability, and alerting (Datadog, Azure Monitor, App Insights)
• • Proven security best practices across pipelines and runtime environments (JFrog, RBAC, secrets)

Responsibilities

• • Design, implement, and maintain CI/CD pipelines for applications, platforms, APIs, batch jobs, and data pipelines
• • Automate model build, test, packaging, versioning, and deployment workflows across dev, test, and production
• • Provision and manage cloud infrastructure (compute, networking, storage) optimized for AI workloads
• • Implement Infrastructure as Code (IaC) using Terraform and/or Bicep
• • Build, deploy, and optimize containerized services using Docker on OpenShift and AKS
• • Establish and maintain monitoring, logging, and tracing across applications, models, and data pipelines
• • Embed security controls into CI/CD pipelines (CodeQL, secrets management, vulnerability detection)
• • Partner with Data Scientists and ML Engineers to streamline the AI/ML lifecycle from experimentation to production

Technologies & Skills