Agentic DevXP: AI-Devops Engineer(Devops+Cloud+AI)

AgenticXP Engineer

To be successful in this role, candidates should demonstrate

• Proven experience designing and executing large-scale Jenkins-to-GitHub Actions migration programs across multiple teams and repositories.
• Strong platform engineering experience, including reusable workflows, CI/CD standards, golden paths, and self-service developer tooling.
• Experience operating and driving adoption across large engineering estates (e.g., hundreds to thousands of repositories and multiple product teams).
• Deep understanding of GitHub platform governance, repository standards, workflow standardization, and enterprise-wide enablement strategies.
• Strong hands-on experience designing deterministic agentic workflows, with automated validation, quality controls, and predictable outcomes.
• Practical expertise applying AI to software delivery, code understanding, migration activities, testing, and developer productivity use cases.
• The ability to balance governance, scalability, developer experience, and platform adoption while influencing engineering teams through clear and highly usable solutions

Job Description (Senior) Agentic DevXP Engineer

Role Purpose

This role modernizes our software delivery platform and evolves Developer Experience (DevXP) toward an AI-enabled, agentic model. It blends CI/CD platform engineering with practical AI application focused on real engineering problems such as pipeline migration, automation, code understanding, and testing enablement. This is not an AI research role.

Core Mission

Enable faster, safer software delivery with minimal friction by building a standardized, AI-enabled developer platform.

Focus Area Description

CI/CD Modernization

Migrating Jenkins to GitHub Actions

Scalability

Developing reusable workflows and standards

Contextual Readiness

Building "agent-ready" repositories

AI Integration

Designing AI-assisted engineering workflows

Governance

Implementing quality gates and guardrails

Empowerment

Driving developer self-service and platform adoption

Cloud

AWS

Key Responsibilities

CI/CD Modernization

• Migrate legacy Jenkins pipelines to GitHub Actions.
• Build reusable workflows, templates, and standards to reduce fragmentation.
• Improve visibility and observability across all delivery flows.

AI-Assisted Engineering

• Apply AI to accelerate migrations, code analysis, testing, and documentation.
• Create safe, repeatable AI workflows backed by robust validation layers.

Agent-Ready Repositories

• Define and implement repository standards covering metadata, documentation, instructions, and templates.
• Ensure AI tools have sufficient context to operate effectively without compromising security.

Agent Workflows & Guardrails

• Integrate AI into engineering workflows across GitHub, CI/CD, Jira, and related systems.
• Define guardrails around access, validation, peer review, and security.
• Focus on high-value, practical use cases that address immediate bottlenecks.

Platform Adoption

• Onboard engineering teams to standardised CI/CD and AI practices.
• Provide golden paths, documentation, and starter templates.
• Drive adoption through iterative feedback loops and user-centric solutions.

Required Experience

CI/CD & Platform Engineering

• Strong hands-on experience with GitHub Actions and Jenkins.
• Proven track record building reusable workflows and developer tooling.
• Proficiency in Python, Bash, TypeScript, or Go.
• Experience with containers, Kubernetes, and cloud-native delivery practices.
• Deep understanding of GitHub workflows including PRs, CODEOWNERS, and repository standards.
• Ability to unify fragmented environments and drive enterprise-wide adoption.

AI & Agentic Practices

• Hands-on experience with LLM-powered tooling such as GitHub Copilot or Claude.
• Practical application of AI to code understanding, automated testing, and migration tasks.
• Experience managing repository-level AI context (e.g., .github/instructions.md or prompt files).
• Solid grasp of AI risks including hallucinations, security vulnerabilities, and over-automation.
• Experience designing safe, human-in-the-loop AI patterns with manual validation checkpoints.

Seniority Expectations