AI - DevOps Architect

AI - DevOps Architect

Experience: 1218 Years
Location: Bangalore

Role Overview

We are looking for an experienced AI-DevOps Architect to lead the modernization of enterprise engineering platforms by combining DevOps best practices with AI-driven engineering capabilities. The ideal candidate will drive CI/CD transformation, establish agent-ready development environments, integrate AI into engineering workflows, and enable teams to adopt scalable, secure, and efficient software delivery practices.

Key Responsibilities

CI/CD Modernization

• Modernize and migrate legacy Jenkins pipelines to GitHub Actions.
• Design and implement reusable workflows, templates, and engineering standards to reduce platform fragmentation.
• Enhance observability, monitoring, and traceability across software delivery pipelines.
• Standardize CI/CD practices across engineering teams and business units.

AI-Assisted Engineering

• Leverage AI technologies to accelerate code migrations, code analysis, testing, and documentation generation.
• Build secure, repeatable AI-driven workflows with strong validation and governance practices.
• Identify and implement high-impact AI use cases that improve engineering productivity.

Agent-Ready Repositories

• Define repository standards, including metadata, documentation, instructions, templates, and governance controls.
• Ensure repositories are structured to support AI-powered tools while maintaining security and compliance.
• Establish best practices for repository organization and developer experience.

AI Agent Workflows & Governance

• Integrate AI capabilities across GitHub, CI/CD platforms, Jira, and related engineering ecosystems.
• Define guardrails for access control, security reviews, code validation, approvals, and compliance.
• Implement human-in-the-loop validation mechanisms to ensure safe and reliable AI adoption.

Platform Enablement & Adoption

• Drive adoption of standardized DevOps and AI engineering practices across teams.
• Develop reusable starter kits, golden paths, documentation, and onboarding frameworks.
• Gather feedback from engineering teams and continuously improve platform capabilities and developer experience.

Required Experience & Skills

DevOps & Platform Engineering

• Strong hands-on experience with GitHub Actions and Jenkins.
• Proven expertise in designing reusable workflows, developer platforms, and automation frameworks.
• Strong programming skills in Python, Bash, TypeScript, or Go.
• Experience with Docker, Kubernetes, and cloud-native application delivery.
• Deep understanding of GitHub ecosystem components, including Pull Requests, CODEOWNERS, branch protection rules, and repository governance.
• Experience leading enterprise-wide CI/CD transformation initiatives.

AI & Agentic Engineering

• Hands-on experience with AI-powered development tools such as GitHub Copilot, Claude, Cursor, or similar platforms.
• Practical experience applying AI to software engineering activities including code analysis, testing, migration, and documentation.
• Expertise in managing repository-level AI context, prompts, instructions, and knowledge assets.
• Strong understanding of AI risks, including hallucinations, security vulnerabilities, data leakage, and over-automation.
• Experience implementing human-in-the-loop validation processes and responsible AI practices.

Cloud & Automation

• Experience with cloud platforms such as Azure, AWS, or GCP.
• Knowledge of Infrastructure as Code (Terraform, CloudFormation, or equivalent).
• Familiarity with DevSecOps practices and security automation.

Leadership Expectations

• End-to-End Ownership: Drive platform modernization initiatives from strategy through execution.
• Execution Focus: Deliver practical tooling, automation, and measurable outcomes.
• Innovation Mindset: Translate emerging AI capabilities into scalable engineering solutions.
• Strategic Thinking: Balance enterprise standardization with project-specific needs.
• Influential Leadership: Lead by example, mentor teams, and drive adoption through tangible results.
• Continuous Improvement: Foster a culture of automation, innovation, and engineering excellence.

Preferred Qualifications

• Experience leading large-scale DevOps transformation programs.
• Exposure to AI-powered software development lifecycle (SDLC) frameworks.
• Experience building Internal Developer Platforms (IDP) and developer self-service capabilities.
• Relevant certifications in Cloud, Kubernetes, DevOps, or AI technologies are preferred.