Senior Backend Engineer (AI), Pipeline Execution

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Senior Backend Engineer (AI), Pipeline Execution | WithMira

Resumen del rol

Senior Backend Engineer (AI), Pipeline Execution

Requisitos y responsabilidades

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Details

Collaborate with Engineering, Product, and UX partners to refine priorities: where we can move faster, where we’re missing data, and where there’s whitespace to innovate.
Contribute to defining what success looks like across our AI agents, ensuring we’re not just shipping, but learning from how features perform in production.
Keep a close eye on the competitive landscape and emerging AI-native DevOps tools, helping us understand what it takes to keep GitLab CI best-in-class in an increasingly agentic world.
AI Pipeline Builder, the foundational CI agent that auto-creates pipelines for new projects and serves as the launchpad for onboarding new CI users.
Automate the Fix a Failing Pipeline flow at scale – from dogfooding on internal GitLab projects through to safe, controlled rollout for customers, solving real infrastructure and scalability challenges.
Build the instrumentation and observability layer that makes agentic CI trustworthy — trigger volume dashboards, retry rates, cost safeguards — so we can measure what’s working, catch what isn’t, and iterate with confidence.
Harden the CI pipeline execution infrastructure that these agents depend on: database access patterns, background processing, and job orchestration built to handle the additional load that AI-driven automation introduces at enterprise scale.
Design, build, and operate backend features that make GitLab CI fast, reliable, and easy to use at scale.
Implement AI-powered and agentic CI capabilities that integrate with GitLab’s Duo Agent Platform.
Instrument, monitor, and improve CI systems using data, observability, and safe rollout practices.
Write secure, well-tested Ruby on Rails code in our monolith, improving existing features while reducing technical debt.
Collaborate cross-functionally with Product, UX, and Infrastructure, mentoring others and raising engineering standards across the Verify stage.
Strong Ruby on Rails backend experience in a large, production codebase.
In-depth experience building and operating AI-powered backend features in production.
A data- and observability-driven approach to diagnosing issues, improving reliability, and validating impact.
Clear written and verbal communication, with a collaborative, mentoring mindset in a remote, async environment.
Hands-on experience building, running, and debugging high-traffic production systems, ideally in CI, workflow orchestration, or adjacent infrastructure-heavy domains.Nice to have
Experience with AI agents or agentic frameworks (for example, LangChain or similar technologies) and building agentic workflows in production environments.
Strong PostgreSQL skills, including data modeling, query tuning, and scaling large tables through proactive performance investigation and remediation.