Staff Software Engineer - NLP

GitLab · Full-time · Posted today

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.

The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.

*Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.

About the role

As a Staff Backend Engineer, you will provide technical leadership across your team and adjacent teams, solving the highest-scope and most complex problems in your area. You will lead large, cross-cutting backend initiatives, drive our modular architecture strategy, and define the standards that let teams move faster without compromising quality, security, reliability, or operability.

This is a technical leadership role that combines deep backend expertise, systems judgment, product judgment, and influence across organizational boundaries. You will work with Product, Frontend, Infrastructure, Security, Data, Engineering Managers, and engineers across product groups, bringing subject matter expertise, and you will do it without relying on formal authority.

Why you’ll love this role

Leverage: Your work multiplies across teams. The platforms, standards, and architectural decisions you lead determine how quickly everyone else can ship.
Genuinely Hard Problems: You’ll lead the modernization of a large monolith toward modular, reusable, appropriately independent systems — at the scale of a platform used by millions of users.
Influence Without Bureaucracy: You’ll shape technical direction across teams through clear written proposals and decision records, and partner with Product and Engineering leadership on platform roadmap and investment trade-offs.
Frontier AI Work: You’ll lead adoption of AI-assisted and agentic engineering workflows and define the review, quality, security, and privacy guardrails that make them safe to rely on.
Autonomy: You’ll thrive in our remote-first, asynchronous organization, where clear written communication and self-direction are the pillars of success.

What you’ll do

Lead Cross-Cutting Initiatives: Lead the technical design and delivery of large backend initiatives that span teams, and identify and remove systemic bottlenecks across product and infrastructure groups.
Own Architecture Strategy: Drive modular backend, service, data, and platform architecture. Lead modernization of the monolith and legacy backends toward modular, reusable, and appropriately independently operated systems — while preventing fragmentation and service sprawl.
Set the Standards: Define and improve standards for APIs, contracts, compatibility, schema evolution, testing, security, performance, observability, operability, and maintainability — plus the build, test, deploy, release, rollback, and production-readiness practices needed to operate modular features safely.
Establish Shared Patterns: Create the patterns for dependency management, data ownership, eventing, failure isolation, service maturity, and operational documentation. Establish Go service patterns and Kubernetes operating practices where they matter to our production estate, and guide Rust adoption where it solves a real systems, security, performance, or supply-chain problem.
Own What You Build in Production: Take part in on-call and incident response for the systems your teams own, act as a technical escalation point during complex incidents, and turn what you learn into architectural and operational improvements that prevent recurrence.
Influence and Partner: Shape technical direction across teams without formal authority, and partner with Product and Engineering leadership on platform-level roadmap decisions and investment trade-offs.
Grow Engineers: Mentor Senior and Intermediate engineers, shepherd technical debt reduction and reusable patterns that improve throughput, and raise the technical capability of the wider team.
Lead AI Adoption: Lead team-level adoption of AI-assisted and agentic workflows, including the quality, security, privacy, and operational guardrails, and help engineers direct, validate, reject, and course-correct agent output.

What you’ll bring

Cross-Team Technical Leadership: A sustained record of technical leadership across more than one team or a broad product area.
Deep Architecture Experience: Deep backend architecture and production experience in complex applications, services, or platforms, including scaling or governing APIs, service platforms, data systems, modular monoliths, or shared backend components.
Modularization in Production: Experience modernizing a monolith or legacy backend architecture in production, and with modular architecture such as bounded contexts, package encapsulation, ports and adapters, service extraction, event-driven boundaries, or an equivalent approach.
Influence Without Authority: A strong ability to create alignment through clear written proposals and decision records, so decisions are documented, understood, and adopted without constant escalation.
Product Judgment: The ability to balance customer outcomes, delivery speed, technical health, reliability, and long-term platform investment.
Mentorship: Experience mentoring engineers and shaping standards through code review, documentation, and example.
Agentic AI Leadership: Production experience with AI-assisted or agentic engineering workflows, including the ability to evaluate and improve how a team adopts them.

Helpful experience

Go services and APIs at scale.
Kubernetes and cloud-native operations, including deployment, scaling, observability, rollback, and production readiness.
Rust adoption or production ownership for systems, security, performance, or platform components.
Ruby/Rails modularization and large-monolith modernization.
PostgreSQL scaling, data partitioning, queues, messaging, or distributed systems.
Security-sensitive product or software supply chain engineering.
Experience across SaaS, single-tenant, self-managed, or air-gapped deployment constraints.

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Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.

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