Staff Backend Engineer, Architecture Engineering: Nonlinear Productivity

Overview

As a Staff Backend Engineer, you'll be the technical anchor for GitLab's Nonlinear Productivity team in the US: the person who decides what "proven" means before something ships, and who helps shape what the team builds next, not just how to build it. It's a from-scratch, generalist team with no dedicated product manager — that ownership starts on day one.

Examples of problems this team takes on:

• Cutting the time it takes to complete a good code review — one that still keeps a human in the loop — by half, using agentic solutions.
• Turning a manual, error-prone release step into an agentic workflow that catches its own mistakes before a human ever has to.

What You'll Do

• Set the technical direction for the team's agentic systems, from how agents are orchestrated to where a step should stay human-owned, and defend those calls once they're tested against real code.
• Discover and prioritize sources of friction across GitLab's SDLC, driving the fix — agentic, process-based, or both — from a rough hypothesis through to a shipped, measured result.
• Work across any part of GitLab's codebase as the problem requires, operating like a small, generalist group rather than one scoped to a single service.
• Apply distributed systems judgment to catch cases where generated code looks correct but breaks under concurrency, at scale, or across deployment topologies (including self-managed, dedicated, and multi-tenant environments), and coach others to do the same.
• Mentor senior and mid-level engineers on agent engineering practices and distributed systems judgment through design reviews and pairing.
• Collaborate with the India-based group a few times a week to align on the roadmap, and represent the team's technical progress to stakeholders in the CTO's organization.
• Serve as a bar raiser for hiring, owning the Technical Leadership round for other Staff-level candidates as the team scales.
• Own a greenfield technical foundation from day one.

What You'll Bring

• Experience building reliable agentic or large language model (LLM)-based systems, including multi-step orchestration, tool use, guardrails, and recovery.
• Ability to work autonomously in unfamiliar codebases and drive solutions from discovery through completion.
• Strong distributed systems and computer science fundamentals, including coordination, consistency, idempotency, rate limiting, failure modes, and degradation under load.
• Proficiency in Go, Rust, or Python, with the ability to read and modify code in the others.
• A track record of delivering results from unclear or incomplete requirements — able to decompose complex problems into concrete, shippable steps.
• Experience designing evaluation frameworks for systems where "looks plausible" and "is actually correct" are different questions.
• A history of unblocking and enabling teammates through design reviews, technical writing, or mentoring, and engaging regularly across teams.