Azure DevOps Engineer

Job Title: Azure DevOps Engineer (AI & Automation)

Location: Noida

Experience: Min 3 Years

Department: Engineering / Infrastructure & Platform

Role Overview

We are looking for a DevOps Engineer to own our core DevOps administration while leading the

implementation of AI-driven development workflows. In this role, you will manage

repositories, establish automated CI/CD pipelines, and design autonomous coding, testing,

and code-review agents using technologies like Claude Code, Anthropic Agent SDK, and

GitHub Copilot Workspace/Agents. You will bridge classical platform engineering with AI

native software development lifecycles.

Key Responsibilities

1. DevOps Administration & Repository Management

• Repository Architecture: Design, enforce, and maintain repository branching strategies

(e.g., Trunk-Based, GitFlow, Feature-Branching) and access governance across

organizations.

• CI/CD Pipeline Engineering: Build, optimize, and secure multi-environment

deployment pipelines using GitHub Actions, GitLab CI, or Azure DevOps with caching

and automated quality gates.

• Infrastructure as Code (IaC): Provision and manage cloud resources using Terraform,

Pulumi, or Bicep, ensuring zero-drift environments.

• DevSecOps Integration: Implement automated secret scanning (e.g., Gitleaks),

dependency vulnerability checks (Trivy/Snyk), and SAST/DAST within CI steps.

2. AI Coding Agent Setup & Branch Workflows

• Coding Agent Deployment: Configure and orchestrate developer AI agents (e.g.,

Claude Code, GitHub Copilot Cloud Agents, or custom agent frameworks) to perform

autonomous task execution across different Git branches.

• Repository Context & Prompts: Author and maintain repository-level context files

(AGENTS.md, CLAUDE.md, custom system prompts, and MCP server integrations) to

steer agents toward project conventions and architecture patterns.

• Multi-Branch Automation: Configure workflow triggers that allow AI agents to pick up

issue tickets, work within dedicated feature/bugfix branches, and automatically draft

PRs.

3. Automated Code Review & Testing Agents

• Code Review Agents: Integrate automated AI code-review agents within pull request

workflows to perform compliance checks, security audits, and style adherence reviews

before human sign-off.

• Automated Testing & QA Agents: Build autonomous testing pipelines where agents

analyze diffs, generate missing unit/integration tests, triage test failures, and suggest

fixes directly in CI.

• Governance & Safeguards: Establish strict safety guardrails, execution sandboxes, and

human-in-the-loop approvals for agent-generated code.

Technical Qualifications

Must-Have Experience

• Core DevOps (2+ Years): Hands-on expertise in CI/CD pipeline building, Docker,

Kubernetes, and IaC (Terraform/Bicep/CloudFormation).

• Git Administration: Mastery of Git internals, branch protection rules, merge strategies,

and repository permissions.

• AI Coding Tools & SDKs: Proven experience configuring or extending GitHub Copilot

(Copilot Workspace, Agent Mode, Custom Instructions/Skills) or Claude (Claude Code

CLI, Anthropic API/SDK, Model Context Protocol).

• Automation Languages: High proficiency in Python, Bash, or TypeScript/Node.js for

building custom hooks, bots, and API integrations.

Nice-to-Have Experience

• Experience building multi-agent orchestrations (e.g., CrewAI, LangChain, or custom

sub-agents).

• Experience with Model Context Protocol (MCP) server setups to connect AI agents with

internal tooling, databases, and monitoring systems.

• Deep understanding of DevSecOps standards and cloud infrastructure cost

optimization.

Expected 90-Day Deliverables

Month 1: Audit existing repos and establish standardized CI/CD templates and branch

protection rules across all development projects.

Month 2: Deploy initial Claude / GitHub Copilot agent workflows for automated PR code

reviews and unit test generation.

Month 3: Fully operationalize an end-to-end agentic workflow where feature tickets can be

assigned to branch-specific coding agents to generate, test, and submit initial pull requests.