AI Engineer, Agents & Developer Pipeline :: Austin, TX (Onsite)

Austin, TX, US • Posted 1 hour ago • Updated 37 minutes ago
Contract W2
On-site
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Kubernetes
  • Devops
  • Production support
  • ReactJS
  • Automation
  • docker
  • Linux
  • Continuous Integration
  • Gitlab
  • Artificial Intelligence
  • Infrastructure Management
  • Event Management
  • Regression Testing
  • Release Engineering
  • Technical Documentation
  • Vector Databases
  • Workflows
  • code review
  • multi-agent systems
  • large language models
  • Testing Skills
  • Diagnostic Skills
  • Reliability
  • Safety Principles
  • Data Logging
  • Application Programming Interfaces (APIs)
  • Python (Programming Language)
  • Systems Development Life Cycle
  • Programming Tools
  • Containerisation
  • Virtual Agents
  • Open Source Technology
  • Triage
  • Build Tools
  • Tooling Assembly and Dismantling
  • Gitlab-ci
  • Administrative Operations
  • Webhooks
  • Ability to Speak in Public
  • Autonomous System
  • Basic Engineering
  • Blogging Skills
  • Codebase
  • Deployment Automation
  • Linux Distribution
  • Programme Evaluations
  • Software Version Control
  • Traceability

Summary

Job Title: AI Engineer, Agents & Developer Pipeline

Location: Austin, TX (Onsite)

Duration: Long- Term Contract

Client: ACL/Windriver

About the Role

As an AI Engineer on this team, you'll design and build autonomous and semi-autonomous agents that operate directly inside our software delivery lifecycle. Your primary focus will be creating agents that plug into GitLab - triaging issues, reviewing merge requests, fixing failing builds, generating tests, and automating repetitive engineering toil - and building the pipeline infrastructure that lets those agents run safely, reliably, and at scale across our Linux distribution's codebase.

What You'll Do

Design, build, and iterate on AI agents that perform real engineering tasks: code review, MR triage, build-failure diagnosis, changelog generation, test creation, and dependency updates

Architect agent workflows using tool-calling, retrieval, and multi-step planning so agents can reason over large codebases and CI logs

Develop and maintain GitLab CI/CD pipeline integrations - custom jobs, runners, and webhooks that trigger agents at the right points in the MR and release lifecycle

Build the guardrails around agent actions: permissioning, sandboxing, approval gates, and rollback paths so agents can act on the pipeline without introducing risk

Instrument agents with logging, tracing, and evaluation so their behavior in production pipelines is observable and measurable

Continuously evaluate agent performance against real MRs and pipeline runs, and iterate on prompts, tool definitions, and orchestration logic to improve reliability

Collaborate with platform and release engineering teams to ensure agent-driven changes meet the same quality bar as human-authored changes

Maintain and extend internal APIs/SDKs that let other teams build their own agents on top of the shared pipeline infrastructure

Contribute to open-source agent tooling and represent the company in relevant upstream communities

Write clear technical documentation on agent capabilities, limitations, and pipeline architecture

What We're Looking For

Required:

3+ years of experience building production software, with hands-on experience building LLM-powered agents or tool-using systems

Strong proficiency in Python, plus experience with GitLab CI/CD (.gitlab-ci.yml, runners, pipelines, webhooks, GitLab API)

Practical experience with agent frameworks or patterns (function/tool calling, ReAct-style planning, multi-agent orchestration) - whether via LangChain, LangGraph, custom orchestration, or similar

Experience integrating LLMs into developer tooling (e.g., automated code review, CI failure triage, test generation)

Solid understanding of CI/CD concepts: build systems, artifact management, deployment gating, and pipeline security

Familiarity with Linux-based development environments and version control workflows

Strong engineering fundamentals: testing, code review, observability, and safe rollout practices for automated systems

Preferred:

Experience building guardrails for autonomous systems (permissioning, sandboxing, human-in-the-loop approval flows)

Familiarity with self-hosted GitLab administration or GitLab Duo / other AI DevOps integrations

Experience with vector databases or retrieval-augmented generation (RAG) for codebase-aware agents

Background in release engineering or build systems for a Linux distribution or large open-source project

Experience with containerization and orchestration (Docker, Kubernetes) for running agent workloads in CI

Contributions to well-known open-source Linux or AI agent projects

Nice to Have

Experience with evaluation frameworks for agent reliability and regression testing

Familiarity with Rust or Go for building performant pipeline tooling

Public speaking, blogging, or conference talks on AI agents, DevOps automation, or the Linux community

Why Join Us

Work on an OS used by millions of developers and enterprises worldwide

Meaningful open-source contributions as part of your day-to-day work

Small, senior team with real ownership over architecture and roadmap

Competitive salary, equity, and benefits

Flexible remote-friendly culture

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90719156
  • Position Id: 2026-12185
  • Posted 1 hour ago
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