Lead Azure DevOps Engineer

• Strong hands-on experience with Azure DevOps, Azure Repos, pipelines, service connections, and CI/CD
• Good experience with Azure hosting services such as App Service, Container Apps, Azure Functions, and/or AKS
• Experience with Microsoft Entra ID, Managed Identity, Service Principals, RBAC, and secure service-to-service authentication
• Experience with Azure Key Vault, Azure Monitor, Application Insights, and Log Analytics
• Infrastructure as Code experience with Terraform or Bicep
• Experience with containerization and Docker
• Good understanding of secure API deployment, environment configuration, networking, and secrets management
• Experience packaging or supporting Azure DevOps extensions is a strong plus
• Familiarity with AI/LLM platforms such as Azure OpenAI, Azure AI Foundry, GitHub Copilot, Claude Code, or similar tools
• Familiarity with MCP servers, agent tools, function calling, or agent integration patterns is a strong plus
• Ability to work in a discovery / MVP / productionization context with evolving requirements

Nice to have:

• Experience supporting AI-assisted SDLC, developer productivity tooling, or internal developer platforms
• Experience integrating AI agents with Azure DevOps work items, repositories, pull requests, pipelines, or test plans
• Experience with GitHub Actions, GitHub Copilot custom agents, or GitHub Enterprise governance
• Understanding of software delivery processes, including backlog refinement, PR review, testing, release management, and defect triage
• Experience working with security teams on AI governance, auditability, and data access controls

• Design and implement the hosting and deployment model for AI SDLC agents and supporting services
• Support productionization of existing AI agent demos, including Azure DevOps extension-based user interfaces, backend services, MCP servers, and Azure DevOps integrations
• Set up secure Azure hosting using Azure App Service, Azure Container Apps, Azure Functions, AKS, or Azure AI Foundry-related components
• Build CI/CD pipelines for agent backends, Azure DevOps extensions, MCP components, configuration repositories, and infrastructure
• Implement infrastructure as code using Terraform or Bicep
• Configure secure authentication and authorization using Microsoft Entra ID, Managed Identity, Service Principals, and Azure DevOps permissions
• Manage secrets and configuration through Azure Key Vault and secure deployment practices
• Support integration with Azure DevOps APIs, Azure DevOps MCP, GitHub Copilot, Claude Code, Azure OpenAI / Azure AI Foundry, and related AI SDLC tooling
• Establish logging, monitoring, and alerting using Application Insights, Log Analytics, and Azure Monitor
• Enable auditability of AI agent actions, including run IDs, requester identity, created/updated work items, tool calls, and operational logs
• Support repository-based governance for prompts, templates, agent configuration, MCP settings, and deployment definitions
• Help define environment separation, release process, rollback approach, and operational runbooks
• Work with Security and Architecture teams to ensure the AI SDLC platform meets enterprise requirements around data handling, identity, access, logging, and compliance