Role Description The impact you will have: - Outcome 1 - Outcome 2 - Outcome 3 - Outcome 4 - Outcome 5 - Outcome 6 What we look for: - Competency 1 - Competency 2 - Competency 3 - Competency 4 - Competency 5 - Competency 6 Company Description Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

• Lead, hire, and develop a team of 4–7 senior engineers across the full GTM AI systems stack — setting a high bar for technical excellence, collaboration, and delivery • Stay hands-on: contribute to system architecture, participate in code and design reviews, pair with engineers on complex problems, and own critical technical decisions for the team's most impactful systems • Own the engineering roadmap for GTM AI systems — partnering with Sales Ops, BizTech, Finance, Legal, and GTM leadership to set priorities, define milestones, and communicate progress • Drive delivery of AI-first GTM systems: agentic AI pipelines, LLM orchestration layers, Salesforce CPQ integrations, real-time Slack applications, and AWS event-driven architectures • Champion engineering quality: establish and uphold standards for code review, testing, observability (distributed tracing, alerting, SLAs), incident response, and documentation • Create a culture of responsible AI development — ensuring the team follows safe data handling practices, maintains audit trails, and builds human-in-the-loop controls from the start • Manage team health: run effective 1:1s, give timely and actionable feedback, unblock engineers, resolve conflicts, and advocate for your team's needs within the broader org • Identify and eliminate systemic sources of friction in GTM workflows — turning recurring manual processes into automated, self-healing systems that scale with the business • Serve as a technical authority in cross-functional conversations — representing the engineering team's perspective to VP- and C-level GTM stakeholders

• Mentoring and growing engineering teams • Working on scheduling products • Leading agile ceremonies • Coaching, mentoring, and onboarding new engineering team members • Identifying future technical needs • Providing feedback and guidance for growth • Hiring engineers for development squads

• Manage a team of experienced frontend, backend, and AI engineers to deliver GitLab Duo Chat roadmap commitments across the DevSecOps lifecycle. • Partner with product and UX teams to define requirements and deliver AI features that address customer needs and improve answer quality. • Participate in technical architecture and development work for systems that run AI agents at scale, with a focus on reliability, performance, and maintainability. • Guide day-to-day execution by setting clear direction, tracking progress against milestones, and removing blockers to keep delivery on schedule. • Coach engineers through feedback, guidance, and development conversations that foster each engineer's growth and overall team performance. • Promote a team culture grounded in curiosity, inclusion, accountability, and steady delivery against team goals. • Improve quality, testing, and performance practices that increase coverage, strengthen observability, and keep AI-powered chat workflows reliable in production.