Staff Backend Engineer, Architecture Engineering: Nonlinear Productivity

- 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, since this team operates 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 that raise the team's collective bar rather than just your own output.

- 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 Chief Technology Officer's organization.

- Serve as a bar raiser for the team's hiring, owning the Technical Leadership round for other Staff-level candidates as the team scales.

- Own a greenfield technical foundation from day one, with your scope and impact free to grow as the team scales.

- 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 take a complex, loosely specified problem and decompose it into a concrete proposal of small, shippable steps.

- Experience designing evaluation frameworks for systems where "looks plausible" and "is actually correct" are different questions, and a track record of raising the quality bar for a team's output, not just your own.

- A history of unblocking and enabling teammates - through design reviews, technical writing, or mentoring - and of engaging regularly with other teams to find where collaboration actually pays off.

Nonlinear Productivity - shortened internally to "NLP," with no relation to natural language processing - is one of GitLab's newest teams: a strategic incubation group that reports into AI Platform leadership under the direct sponsorship of the CTO. It's split into a US group (this role) and an India-based group working the same charter; the two sync on roadmap and tooling a few times a week but otherwise run day to day on their own.

Solutions that prove out internally are the team's path to a monetized, customer-facing GitLab offering.

It's a good fit for engineers who want technical ownership of something with no existing playbook, and a hand in defining a brand-new part of GitLab from its first commit.