AI Central - Senior Devops AI Engineer
Zensar Technologies · IT Services & Consulting
- India
- On-site
- Posted today
- Apply by 4 Oct
- Data & AI
About the job
Roles & Responsibilities :
GitHub Actions at scale: reusable workflows, composite actions, self-hosted runners, matrix builds, caching.
GitHub Enterprise working knowledge: organization and repository configuration, rulesets and branch protection, GitHub Apps and fine-grained tokens.
Building agentic developer workflows end to end — an agent that takes a defined input, changes code, runs validation and opens a pull request. GitHub Copilot coding agent, Copilot CLI, custom instructions and skills preferred; equivalent experience with other agent frameworks acceptable if the candidate is willing to work entirely in the GitHub toolchain.
Designing guardrails and evaluating agent output quality — knowing when a generated change is safe to put in front of a reviewer.
Build engineering across mixed technology stacks: able to get an unfamiliar build working, keep it working in CI, and reason about toolchain and dependency management in more than one ecosystem.
Scripting: Python, plus Bash and/or PowerShell.
Nice To Have :
Model Context Protocol (MCP) server authoring.
Secure software supply chain: artifact signing, SBOM, dependency provenance.
JFrog Artifactory.
Prior work productizing internal developer tooling for other teams (platform engineering, not consulting delivery).
GitHub Actions at scale: reusable workflows, composite actions, self-hosted runners, matrix builds, caching.
GitHub Enterprise working knowledge: organization and repository configuration, rulesets and branch protection, GitHub Apps and fine-grained tokens.
Building agentic developer workflows end to end — an agent that takes a defined input, changes code, runs validation and opens a pull request. GitHub Copilot coding agent, Copilot CLI, custom instructions and skills preferred; equivalent experience with other agent frameworks acceptable if the candidate is willing to work entirely in the GitHub toolchain.
Designing guardrails and evaluating agent output quality — knowing when a generated change is safe to put in front of a reviewer.
Build engineering across mixed technology stacks: able to get an unfamiliar build working, keep it working in CI, and reason about toolchain and dependency management in more than one ecosystem.
Scripting: Python, plus Bash and/or PowerShell.
Nice To Have :
Model Context Protocol (MCP) server authoring.
Secure software supply chain: artifact signing, SBOM, dependency provenance.
JFrog Artifactory.
Prior work productizing internal developer tooling for other teams (platform engineering, not consulting delivery).