• Leads the execution of deliverables with the risk and engineering teams ensuring projects are completed on time and within predefined requirements and budgets. • Accountable for team performance within assigned projects, including software engineering and MLOps initiatives. • Serves as subject matter expert on multiplatform applications and ML infrastructure, determining course of action under the direction of systems leadership. • Directs the system development lifecycle including the design, coding, testing, documentation, maintenance, and support of proprietary and purchased software systems and applications. • Leads the design, implementation, and scaling of enterprise MLOps platforms and capabilities, including CI/CD pipelines for ML, model versioning, automated testing, monitoring, and model lifecycle management. • Establishes best practices for model deployment, observability, performance monitoring, drift detection, and retraining strategies. • Partners with Data Science, Risk, Compliance, Legal, and Information Security teams to ensure machine learning systems meet regulatory, governance, and risk management requirements. • Implements and oversees ML governance frameworks including model documentation, validation, explainability, auditability, fairness/bias monitoring, and model risk management controls. • Ensures adherence to enterprise data governance, privacy, and AI risk policies, including responsible AI standards. • Recommends innovation and improvements to policy or procedures; has the latitude to make decisions affecting mid- to long-term operational results. • Develops long- and short-term business and technology strategies aligned to AI/ML roadmaps. • Responsible for managing operating costs and budgets, including infrastructure investments for ML platforms. • Makes decisions on pay, performance, appraisals, schedules, discipline, and hiring. • Builds and leads a high-performing MLOps and engineering organization, establishing clear career paths and leadership development for managers and senior engineers.

• Lead the Design System team, focusing on improve other teams productivity and design consistency; • Design and implement straightforward solutions to complex scenarios, ensuring scalability, maintainability, performance and accessibility; • Work closely to Design and Engineers to define process on attending demands, and guarantee deadlines; • Serve as a focal point in the communication with other teams and areas of the company; • Serve as a technical reference to the team and gain recognition as such across the company; • Mentor and guide other engineers, fostering a culture of technical excellence, ownership, and collaboration; • Live the mission: inspire and empower others by genuinely caring for your own wellbeing and your colleagues. Bring wellbeing to the forefront of work, and create a supportive environment where everyone feels comfortable taking care of themselves, taking time off, and finding work-life wellness.

• Lead the new Engineering, Architecture and Transformation pillar as part of the ELT, setting a clear vision for horizontal engineering excellence across GitLab. • Drive the definition, adoption and continual improvement of engineering best practices, partnering with Product, PMO and vertical engineering leaders to raise quality, reliability and delivery consistency. • Own the "Customer Zero" charter by championing internal use of GitLab, unblocking teams and directly contributing to code when needed to validate workflows and accelerate critical initiatives. • Define and guide the transition to next-generation, AI-optimized architecture, including the design and rollout of core primitives that enable vertical teams to decouple legacy systems and scale for ultra-scale customers. • Build and lead the Architecture, Quality and Engineering Excellence team to deliver non-linear productivity gains through AI-assisted development, including tools such as Claude Code and GitLab Duo. • Establish and manage the Horizontal Engineering team as a flexible, embedded group that joins target teams, gains deep context in their codebases and delivers high-impact features and fixes during US business hours. • Collaborate across the ELT and senior leaders to identify systemic horizontal challenges, prioritize cross-cutting initiatives and ensure clear technical ownership and accountability for their execution. • Champion an operationally frugal mindset by aligning AI and architectural decisions with cost of goods sold optimization, while maintaining high availability, service reliability targets and a strong culture of engineering excellence.

• Lead, mentor, and manage your team through the successful delivery of valuable customer software • Drive collaboration across technology teams to foster innovation • Strengthen and drive engineering processes using TDD, BDD, Microservice, and Vertical Slice Architectures • Partner closely with Product Management to provide technical guidance on software design • Support live applications by promoting proactive monitoring and rapid incident response