Senior Director, Enterprise Architecture and AI

An overview of this role

As the Senior Director, Enterprise Architecture and AI, you will define and govern how GitLab's internal systems connect, integrate, and evolve to support our rapidly scaling business. Reporting to the CIO and serving as a key member of the CIO leadership team, you will lead our Integration, RPA, and AI Engineering teams, setting the architectural standards, governance frameworks, and strategic vision that keep our technology landscape coherent, scalable, and aligned with business objectives. This role is both deeply strategic and hands-on: you will shape the long-term architecture while staying close enough to the work to guide critical technical decisions across teams.

As the architectural leader for GitLab's internal technology ecosystem, you will establish and lead our Architecture Review Board, partnering early and often with system owners so architecture becomes an enabler rather than a gate. You will rationalize our automation and integration landscape, clarify when to use AI, RPA, or traditional integration, reduce shadow IT and software sprawl, and drive clear patterns for data flows and system-of-record designations. In close partnership with the Director of AI Engineering and the CIO, you will be accountable for internal AI strategy and delivery, ensuring AI initiatives are secure, compliant, and integrated with core enterprise platforms while delivering measurable impact across sales, customer success, support, and operations. You will also set direction for how we use modern AI technologies like vector databases, large language models, fine-tuning, and prompt engineering to transform internal workflows while maintaining SOX compliance and strong security controls.

What you'll do

• Define and drive GitLab's enterprise architecture strategy, setting clear principles and patterns for how internal systems connect, integrate, and scale across platforms like Salesforce, NetSuite, Zuora, Workato, and other core business applications.
• Establish and lead GitLab's Architecture Review Board, engaging early with system owners and project teams to shape technical approaches, guide integration patterns, and ensure architectural decisions align with enterprise standards and business objectives.
• Design and govern integration architectures and data flow patterns, including API-first approaches, point-to-point integrations, and data warehouse and reverse ETL models, in close partnership with Data Governance and other cross-functional stakeholders.
• Co-own internal AI program strategy and delivery with the Director of AI Engineering and CIO, ensuring AI initiatives are architected for scalability, compliance, and measurable business impact across sales, customer success, support, and operations.
• Create and execute a cohesive automation strategy that spans agentic AI, robotic process automation (RPA), and traditional integration technologies, rationalizing existing investments and defining clear decision frameworks for tool selection.
• Lead efforts to reduce shadow IT and software sprawl by implementing software governance processes, partnering with system owners to centralize fragmented solutions, eliminate redundant capabilities, and reduce technical debt and unnecessary spend.
• Ensure enterprise, integration, and AI architectures meet SOX compliance and security requirements, including robust access controls, data governance, and audit-ready integration patterns that balance risk management with business agility.
• Align decentralized system roadmaps with enterprise architecture strategy, systematically identify and address technical debt, and provide hands-on technical leadership and mentorship to Integration, RPA, and AI Engineering teams to elevate architectural thinking and execution.

What you'll bring

• Extensive experience defining and governing enterprise architecture in complex, matrixed organizations, including leading architecture strategy across core business systems such as ERP, CRM, CPQ, billing, and financial platforms.
• Deep technical background across integration, automation, and AI, with the ability to step into Architecture, Integration, RPA, or AI Engineering teams and contribute meaningfully to design discussions and problem solving.
• Proven track record building and scaling AI and automation programs, including hands-on familiarity with modern AI technologies such as vector databases, large language models, fine-tuning, prompt engineering, and agentic workflows.
• Expert-level knowledge of data modeling, integration architecture patterns, and API design, including experience designing integration strategies that support both operational and analytical use cases.
• Strong experience establishing and leading architecture review boards or similar governance frameworks, balancing partnership-oriented engagement with clear, enforceable standards.
• Demonstrated success reducing shadow IT and software sprawl through thoughtful software governance, portfolio rationalization, and roadmap alignment with enterprise architecture principles.
• Deep understanding of SOX compliance, internal controls, and security architecture for business applications, with experience designing audit-ready integration and automation patterns.
• Exceptional communication and influencing skills, with the ability to engage VP and C-level stakeholders, translate complex architectural concepts into clear business language, and drive alignment across decentralized teams.

The Enterprise Architecture and AI team at GitLab is responsible for designing, governing, and evolving the internal technology landscape that powers our business. We define how our core systems connect, integrate automation and AI into everyday workflows, and ensure our architecture is scalable, secure, and aligned with company priorities. Composed of experienced architects and engineers across integration, RPA, and AI, we operate asynchronously and partner closely with system owners in functions such as Sales, Finance, Customer Success, and Operations. We focus on setting clear architectural standards, rationalizing tools and automation, and guiding teams in using modern AI technologies to deliver measurable business impact while maintaining strong compliance and security practices. For more on how we work, see the Enterprise Applications Team Handbook Page.