GitLab - Senior Solutions Architect, AI / Core DevOps - EMEA
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Requirements
• Deep interest and hands-on experimentation in how AI is changing the software development lifecycle, especially in core DevOps workflows. • software development lifecycle • core DevOps • core DevOps • Strong technical foundation in modern software delivery practices, including automation, continuous integration and continuous delivery, and cloud-native or platform-oriented environments. • Ability to speak thoughtfully about architectural and operational tradeoffs, including Kubernetes, monolithic versus microservices architectures, and monorepo versus polyrepo approaches. • Kubernetes • Kubernetes • monolithic versus microservices architectures • monorepo versus polyrepo • Experience guiding technical strategy with customers, internal stakeholders, or engineering teams in a way that is practical rather than purely theoretical. • Clear communication skills with the ability to explain complex technical ideas to different audiences. • Comfort working effectively with minimal oversight as a manager of one in a remote, asynchronous environment while staying closely aligned with a global team. • Openness to candidates from different backgrounds, including practitioners, senior solutions architects, or technical experts with transferable expertise in AI and DevSecOps. • The AI subject matter expert joins a small global team within GitLab's Solutions Architecture organization that provides deep domain expertise aligned to GitLab's product areas. We are built to link fast-moving AI innovation with the realities of customer environments and modern software delivery. Rather than staying at a high level, we focus on practical technical depth and help translate emerging ideas into useful guidance. • AI subject matter expert • This role is specifically aligned to core DevOps, alongside peers focused on other areas such as platforms and security and compliance. We work across regions and collaborate closely with product-aligned functions, making this a strong fit for someone who enjoys working across technical boundaries while staying grounded in hands-on knowledge. Our challenge is to keep pace with rapid change in AI while remaining clear, credible, and useful to the people building and operating software every day. • core DevOps • core DevOps • For more on how GitLab works, see the GitLab Handbook. • How GitLab Supports Full-Time Employees • Benefits to support your health, finances, and well-being • Flexible Paid Time Off • Team Member Resource Groups • Equity Compensation & Employee Stock Purchase Plan • Growth and Development Fund • 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. • Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. • Country Hiring Guidelines:
Responsibilities
• Serve as GitLab's AI subject matter expert for core DevOps, bringing technical depth and practical guidance to customer and internal conversations. • AI subject matter expert • core DevOps • core DevOps • Partner with customers and field teams to map AI use cases to real software development lifecycle challenges and recommend approaches that improve developer productivity, delivery speed, or operational reliability. • Develop and share informed perspectives on the future of AI in software development, including emerging concepts such as more automated delivery workflows. • Engage with product-aligned teams to ensure your domain expertise reflects how GitLab organizes and evolves its platform capabilities. • Evaluate and discuss architectural tradeoffs such as monoliths versus microservices and monorepos versus polyrepos in the context of AI-enabled development. • monoliths versus microservices • monorepos versus polyrepos • Draw on hands-on experience with modern DevOps tooling and automation, including areas such as continuous integration and continuous delivery, to inform strategic discussions. • continuous integration and continuous delivery • Collaborate asynchronously with teammates across regions to share findings, align recommendations, and keep customer and product work moving forward. • Contribute to a streamlined interview and collaboration culture that values clear communication, iteration, and practical results.
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