Staff Forward Deployed Engineer

Staff Forward Deployed Engineer, Agentic SDLC

An Overview of This Role

GitLab’s Forward Deployed Engineering team is a field-situated product engineering function focused on strategic customer outcomes, AI adoption, and direct contribution back to GitLab’s product. This is not a traditional field engineering, solutions architecture, or professional services role. The Staff Forward Deployed Engineer is expected to operate with deep customer proximity while maintaining the technical bar and contribution discipline of a Staff-level product engineer.

This role exists where strategic customer urgency, complex technical ambiguity, and GitLab product execution intersect. The Staff FDE will work directly with strategic customers, Product, Engineering, Support, SRE, SA, CSA, CSM, and Professional Services to diagnose and resolve high-impact adoption blockers, contribute production-grade fixes and features, and convert learning into repeatable patterns for GitLab and its customers.

The ideal candidate is a Staff-level product or platform engineer with strong Ruby/Rails, Go, systems, DevSecOps, and AI adoption experience who can operate credibly in front of senior customer stakeholders while also contributing directly to GitLab’s core product.

Why This Role Exists

Strategic customers sometimes encounter challenges that are too broad, deep, urgent, or cross-functional for any single existing team to own end-to-end. These challenges may involve product gaps, performance degradation, scale bottlenecks, AI governance, adoption blockers, architectural constraints, Git usage patterns, CI/CD complexity, API automation, security requirements, or operational instability.

FDE provides technical stewardship in these moments. The team does not simply observe, report, or escalate. FDE engages directly, diagnoses the real technical problem, collaborates with the right internal teams, contributes code or technical solutions where appropriate, and transitions the outcome back into normal ownership once the customer is stabilized and the learning is reusable.

Core Responsibilities

Product Contribution

• Contribute production-quality code to GitLab’s product and adjacent systems.
• Develop bug fixes, features, integrations, tooling, or performance improvements where strategic customer outcomes require direct engineering contribution.
• Work within GitLab’s normal product and engineering processes, including issue discovery, MR creation, testing, review, documentation, and maintainability.
• Influence Product and Engineering to ensure customer-driven solutions align with long-term product direction and do not become one-off customizations.
• Translate field-discovered blockers into durable product improvements, reference architectures, documentation, or repeatable implementation patterns.

Strategic Technical Stewardship

• Engage with strategically important customers when adoption, retention, executive confidence, or public trust is materially at risk.
• Diagnose complex technical problems across GitLab product behavior, customer architecture, Git internals, CI/CD workflows, API usage, observability, infrastructure, networking, and cloud environments.
• Coordinate across Product, Engineering, SRE, Support, SA, CSA, CSM, PS, and customer technical teams to drive end-to-end resolution.
• Provide data-driven, trace-level, systems-level recommendations for improving GitLab usage, workflows, automation, and architecture.
• Ensure FDE involvement creates durable outcomes rather than permanent dependency.

AI Adoption and Agentic SDLC

• Drive adoption of GitLab Duo Agent Platform with strategic customers in governed, measurable, production-oriented ways.
• Identify and resolve blockers to AI adoption, including governance, usage controls, auditability, security, compliance, operating model, workflow design, and integration gaps.
• Develop customer-safe adoption patterns for agentic SDLC, AI-assisted development, intent-based review, AI governance, and human-in-the-loop software delivery.
• Partner with Product, Engineering, Field, and Customer Success to translate AI adoption learning into reusable guidance and product improvements.

Thought Leadership

• Lead GitLab in creating industry-shaping technical narratives grounded in real customer experience and product reality.
• Contribute to Well Architected Frameworks, whitepapers, webinars, reference architectures, technical strategy memos, and adoption frameworks.
• Steward ideas from discovery through formulation, validation, amplification, and normalization across the company.
• Partner with SA, CSA, Product, Engineering, Marketing, PMM, CSM, Support, and executive stakeholders to make thought leadership a company capability rather than an isolated team activity.

Required Qualifications

• Staff-level experience building, operating, or improving complex production software systems.
• Demonstrated ability to contribute to large, mature product codebases with high standards for testing, maintainability, performance, and security.
• Strong Ruby/Rails or Go experience, with ability to contribute directly to GitLab’s product contribution surface.
• Experience diagnosing complex system behavior across application code, data stores, infrastructure, observability, networking, APIs, and customer usage patterns.
• Deep understanding of modern DevSecOps workflows, including Git, merge requests, CI/CD, security controls, compliance needs, and enterprise software delivery.
• Experience working with strategic customers or senior technical stakeholders in ambiguous, high-impact situations.
• Ability to coordinate across Product, Engineering, Support, SRE, SA, CSA, CSM, Professional Services, and customer teams without formal authority.
• Strong written communication skills, including the ability to produce technical narratives, architecture guidance, and reusable field/product assets.
• Demonstrated judgment in distinguishing reusable product/platform work from customer-specific customization.

Strongly Preferred Qualifications

• Direct experience with GitLab as a platform, including GitLab.com, Dedicated, or self-managed deployments.
• Production experience with Ruby on Rails, Go, PostgreSQL, Redis, Sidekiq, Vue, TypeScript, Kubernetes, Docker, Linux, and observability tooling.
• Deep familiarity with Git internals, repository performance, large-scale Git usage patterns, or CI runner behavior.
• Experience with AI-assisted software development, agentic workflows, AI governance, model evaluation, context management, prompt/workflow design, or AI adoption in regulated enterprise environments.
• Experience creating thought-leadership artifacts such as whitepapers, technical talks, architecture frameworks, RFCs, public technical writing, or internal strategy documents.
• Background in performance engineering, SRE, platform engineering, infrastructure engineering, or distributed systems.
• Experience working in open-source or highly asynchronous engineering environments.

Technologies and Domains

Directly relevant technologies include:

Ruby / RailsGo (GoLang)AI-assisted development and agentic SDLC

• PostgreSQL
• Redis / Sidekiq
• Git internals
• GitLab CI/CD and Runner architecture
• Kubernetes and containers
• Terraform
• Linux, networking, observability, and performance analysis
• Vue / TypeScript
• APIs and automation
• DevSecOps governance, security, and compliance

Experience with Java, .NET, or other enterprise application stacks may provide useful customer context, but is not a substitute for the ability to contribute directly to GitLab’s core product and adjacent systems.

What This Role Is Not

This role is not:

• a generic field engineering role
• a proof-of-concept factory
• a replacement for SA, CSA, CSM, PS, Support, SRE, Product, or Engineering
• a customer-specific customization function
• unbilled Professional Services
• a requirement-gathering role that only escalates to Product
• an AI evangelism role disconnected from product execution

Success Measures

Success in this role may include:

• Strategic customer adoption or retention risks stabilized.
• Product bugs fixed or features contributed.
• AI adoption blockers removed for strategic accounts.
• Reusable implementation patterns created and handed off.
• Well Architected Frameworks, whitepapers, webinars, or technical narratives produced or enabled.
• Cross-functional customer challenges resolved without creating permanent FDE dependency.
• Product, Engineering, Support, CSA, CSM, PS, and SA teams equipped with better guidance from field-discovered learning.
• Increased adoption and effective usage of GitLab capabilities, especially GitLab Duo and Duo Agent Platform, in targeted accounts.

Ideal Candidate Profile

The ideal candidate is a Staff-level product or platform engineer who can operate in the field without becoming “field only.” They are equally comfortable reading traces, writing production code, debugging architecture, discussing AI governance, leading a customer technical session, opening a merge request, writing a whitepaper outline, and coordinating across internal teams to achieve a strategic customer outcome.

They are not simply a strong communicator with technical awareness. They are a deeply credible engineer with the judgment, presence, and narrative ability required to turn customer reality into product contribution, adoption guidance, and company-level thought leadership.