
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in Remote - Canada"), this listing's salary midpoint is about 90% lower. The offer sits below the benchmark range (€5,934–€22,698). The listed pay band (€1,065–€1,727) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 4 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Backend Engineer | €3,600/per month | €6,511/per month | €15,826/per month |
| All roles in Remote - Canada | €5,934/per month | €12,118/per month | €22,698/per month |
| Pay in our data — not quoted in ad (Senior) | €1,065/per month | €1,396/per month | €1,727/per month |
As a Staff 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. Some examples of the 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, 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. 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 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.
Job Details
Responsibilities
- Set technical direction for agentic systems and orchestration
- Identify and fix friction in GitLab's SDLC using agentic or process-based solutions
- Work across the entire GitLab codebase as a generalist
- Apply distributed systems judgment to ensure scalability and concurrency
- Mentor senior and mid-level engineers on agent engineering and distributed systems
- Collaborate with India-based team on roadmap and report to CTO organization
- Lead technical leadership interviews for Staff-level candidates
- Own a greenfield technical foundation
Requirements
- Experience building reliable agentic or large language model (LLM)-based systems
- Ability to work autonomously in unfamiliar codebases
- Strong distributed systems and computer science fundamentals (coordination, consistency, idempotency, rate limiting)
- Proficiency in Go, Rust, or Python
- Track record of delivering results from unclear or incomplete requirements
- Experience designing evaluation frameworks for AI systems
- History of mentoring and enabling teammates
Skills & Technologies

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