Staff Enterprise Architect

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.

An overview of this role

As a Staff Enterprise Architect, you will design and evolve how GitLab's internal systems are configured, integrate, perform and scale to support a rapidly growing business. Reporting to the Director, Enterprise Architecture and AI Intelligent Automation, you will apply all four architecture lenses (business, application, data, and technology) to the systems in your scope, treating AI as a standing consideration inside each rather than a separate workstream.

Enterprise-wide strategy, portfolio direction, and standards ownership sit with the Director. Your job is depth: turning that direction into designs detailed enough to build, and being the person trusted with the hardest technical problems in the enterprise. You will not manage people. You will lead through architecture, as the partner to our Applications engineering teams and to Integration, RPA, and Intelligent Automation, and as a reviewer on the Architecture Review Board, where the aim is to make architecture an enabler rather than a gate.

What you'll do

Business architecture

In collaboration with product management and process owners, map the current-state processes and capabilities supported by the systems in your scope, tying each capability to its supporting systems, owners, and systems of record, and identify and resolve where those systems create friction, manual handoffs, or duplicated work, including handoffs an AI agent could remove entirely.

Architect end-to-end processes that span front-office and back-office systems, including new product introduction, CPQ and quote-to-cash, billing and revenue recognition, renewals, and record-to-report, together with the customer service processes that run alongside them, including case and escalation management, entitlements, and service level commitments, rather than optimizing any one system in isolation.

Redesign workflows before automating them, so we aren't encoding broken processes into new tooling. For each step, decide what an AI agent should handle, what deterministic automation should handle, and what stays with a person.

Application architecture

In collaboration with the Applications engineering teams, serve as their embedded architect, producing high level designs and patterns for changes to Salesforce, NetSuite, Zuora, Zendesk, and other core platforms. Favor configuration and supported extension patterns over customization, evaluate each platform's native AI before anything bespoke is built, and keep system roadmaps aligned with enterprise standards.

Design for maintainability and supportability: clear service ownership, observability and error handling in integrations, documented runbooks, and realistic total cost of ownership.

Go deep on the platforms in your scope, staying current on release notes, published limits, API behavior, and known constraints, so designs account for what the platform will actually do rather than what the documentation promises.

Govern application change by reviewing significant build proposals, data model changes, and third-party package additions before they are committed, giving teams a clear and timely decision, and keeping platforms on supported versions and ready to upgrade.

In collaboration with each domain's technical lead, or the vendor where that is the better source, run quarterly health checks on Salesforce, NetSuite, Zuora, Zendesk, and Workato, measuring customization footprint against each platform's published ceilings for API and governor limits, automation, storage, transaction and ticket volumes, AI consumption, and licenses. Publish a report card showing headroom, what is trending toward a limit, and who owns the fix.

Data architecture

Architect data flows across operational and analytical planes, including the retrieval and grounding patterns that make enterprise data usable by AI, alongside API-first integrations, event-driven patterns, batch pipelines, data warehouse models, and reverse ETL back into business systems.

Design data access and handling patterns that meet privacy, residency, and SOX requirements, setting explicit boundaries on what AI models and agents may read, retain, or act on, plus field-level controls for sensitive customer and financial data.

Establish integration and data contracts between systems, so downstream consumers aren't adversely affected by upstream schema changes.

Technology architecture

Define platform and integration patterns for the systems in your scope, spanning iPaaS (Workato), identity and access management, secrets handling, and the cloud services those systems depend on. Define how each system exposes its capability to AI agents, through APIs, tool interfaces, and scoped permissions.

In collaboration with Infrastructure, design for reliability and scale, covering environment strategy, sandbox and test data management, and non-functional requirements, while CI/CD and disaster recovery remain theirs to own.