Summary
✨ AI‑Generated
A DevOps engineering role supporting the delivery and operational readiness of AI-enabled solutions. The position focuses on secure cloud deployment, CI/CD pipelines, container orchestration, API and MCP endpoint setup, identity management, and coordination across technical and security teams.
Highlights
Work on AI-enabled solutions with modern Azure infrastructure, secure deployment practices, CI/CD automation, and collaboration across engineering, security, and vendor teams.
Description
Job Description:
DevOps Engineer supporting delivery, deployment, and operational readiness of AI enabled solutions.
Translates stakeholder requirements into technical specifications, documents CI/CD and deployment processes, and coordinates with engineering, security, and vendor teams to deliver securely on Azure.
Required Skills
CI/CD Enablement: Document and support CI/CD pipelines using GitHub Actions (or Azure DevOps) — branching strategy, build/test gates, artifact versioning, DEV→TEST→UAT→PROD promotion, approvals, and rollback.Azure & AKS Deployment: Support deployment and configuration on Azure, including AKS, Container Registry, Key Vault, API Management, and managed identities; working knowledge of Helm, manifests, and secrets handling.API & MCP Setup: Analyze, document, and coordinate setup of APIs and MCP servers/endpoints — tool definitions, schemas, authentication (OAuth 2.x / OIDC / Entra ID), rate limiting, versioning, and gateway registration.- strongly preferred but not requiredDevSecOps & Compliance: Embed security controls into the delivery lifecycle — vulnerability and container image scanning, secrets management, audit logging, and remediation tracking to closure.Release Coordination: Maintain release calendar; coordinate change and deployment windows across internal teams and vendors; ensure environment configuration is consistent and reproducible.Quality Assurance: Define and execute test and validation plans (functional, integration, regression) and verify results prior to release sign-off.Documentation: Produce and maintain system designs, deployment runbooks, operations guides, configuration baselines, and troubleshooting procedures.Monitoring & Readiness: Support observability setup (Azure Monitor, Log Analytics, Application Insights) and define alert thresholds and escalation paths.
Qualifications
Education: Bachelor's degree in Computer Science, Information Systems, Engineering, or related field; Master's preferred.Experience: Minimum 3 years as a DevOps Engineer with hands-on cloud deployment exposure; 1+ year on AI mpreferred, data platform, or API-driven projects preferred.CI/CD & GitHub: Practical experience with GitHub Actions, repositories, pull request workflows, branch protection, and release management (Azure DevOps accepted as equivalent).Cloud & Containers: Working familiarity with Azure and containerized deployment on AKS/Kubernetes; Docker and IaC (Terraform, Bicep, ARM) a plus.APIs & Integration: Understanding of REST/API design, API gateways, OAuth 2.x / OIDC / SSO patterns; familiarity with MCP or comparable agent/tool integration standards.Technical Skills: Python preferred (Java, R, or PowerShell acceptable); comfort with YAML, JSON, Git, kubectl, and Azure CLI.
Familiarity with AI/LLM concepts a plus.
