Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
The Woodlands, TX, United States
Posted
Yesterday
GitAWSBashGitHub ActionsGitLab CIGoogle CloudJenkinsPowerShellPythonVaultGenerative AIAzureNode.jsReactJavaScriptTypeScriptCI/CDAzure DevOps
Job Description
"Job Title: Full Stack AI Developer
Work Location: Hybrid in The Woodlands, TX
Duration: 1 year with option to extend or convert
Job Description & Responsibilities :
- Build, configure, and maintain Azure Pipelines (YAML) with build, test, and deploy stages across dev, staging, and production.
- Configure Azure Repos branch policies, pull request validation builds, and release approvals.
- Manage pipeline variables, variable groups, service connections, and secrets (e.g., Azure Key Vault) to team security standards.
- Wire automated tests, linting, and security and quality scans into pipelines as release gates.
- Help build reusable pipeline templates and environment provisioning scripts so new platform instances deploy consistently.
- Support feature flag and configuration management across environments.
- Troubleshoot failed builds and deployments, and document the root cause and fix.
- Use AI coding agents and assistants to draft pipeline definitions, scripts, and docs, then validate the output before merging.
- Maintain runbooks, pipeline documentation, and onboarding notes.
- Track work in Azure Boards, take part in code reviews, and join sprint ceremonies.
- Contribute small fixes across the stack (TypeScript/React front end, Node or Python APIs) as capacity allows.
Skills & Qualifications:
- 1-3 years of professional experience in software development or DevOps, or equivalent internships or projects.
- Hands-on exposure to Azure DevOps (Pipelines, Repos, Boards) or a comparable CI/CD tool (GitHub Actions, GitLab CI, Jenkins).
- Working Git knowledge: branching, pull requests, resolving merge conflicts.
- Able to read and write YAML, with basic scripting in Bash or PowerShell.
- Familiarity with TypeScript/JavaScript and at least one of Node.js or Python.
- Basic cloud fundamentals (Azure preferred; AWS or Google Cloud Platform acceptable): compute, storage, identity and access.
- Daily, practical use of AI development tools (e.g., GitHub Copilot, Claude Code, Cursor), with the judgment to review and test what they produce.
Clear written communication and habitual documentation
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