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 robust 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.

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