Strategy & Execution Manager, GTM

CSQ227R245 Strategy and Execution Manager, GTM The Strategy Execution Manager is responsible for operationalizing Services and Enablement strategy using AI. You will lead the optimization of programs, financial planning, and cross-functional initiatives to scale the business for continued hyper-growth. This role is unique: you will bridge the gap between high-level executive strategy and technical execution, specifically by leveraging AI automation to streamline Services and Enablement delivery, improve margins, and automate complex internal workflows. The ideal candidate has not just worked with AI tools — they have built end-to-end AI-powered solutions using the modern AI and data stack and brings firsthand experience shipping production-grade systems. Impact You Will Have Drive Executive Decisions: Lead business case analysis to determine investments across countries, verticals, and cloud service providers for the Services and Enablement organization Architect AI-Driven Operations: Own the end-to-end lifecycle of AI deployments (ideation to QA) designed to automate Services and Enablement workflows Translate Strategy to Scale: Convert long-range planning into measurable KPIs, building automated dashboards that provide real-time visibility into organizational health Optimize GTM Delivery: Develop actionable frameworks to align GTM teams, ensuring Services and Enablement offerings are positioned effectively against competitors and integrated into the broader product roadmap Build, Not Just Advise: Design and personally ship AI agents, pipelines, and internal tools — you will be expected to own the full solution lifecycle, not just define requirements Key Responsibilities Strategic Planning Execution — Support Long Range Planning, OKRs, and identifying risks in planning assumptions for the Services and Enablement organization AI Process Automation — Identify inefficiencies within the Services and Enablement lifecycle and build AI agents to address them. You will be hands-on in the build — from prompt engineering and RAG pipelines to agent orchestration and evaluation frameworks Modern Data Stack Ownership — Architect and maintain the data infrastructure underlying operational dashboards and AI systems, using tools Databricks native stack Cross-Functional Leadership Enablement — Act as the connective tissue between Senior Sales, Services, and Enablement Leadership and technical teams What We Look For Experience: 7+ years in Strategy, Operations, or Product Leadership, with at least 3 years of hands-on experience building AI-powered solutions or data products in production environments AI Builder (Required): Demonstrated track record of designing and shipping end-to-end AI solutions. Experience with Foundation Model APIs is strongly preferred Modern Data Stack Proficiency (Required): Fluency across the modern data stack — including Databricks, Spark, Delta Lake, and cloud data warehouses. Ability to write production-quality SQL and Python Strategic Mindset: Proven ability to interpret complex data sets (e.g., cloud infrastructure costs, market sizing) to derive actionable investment insights Technical Depth Meets Business Acumen: Comfortable owning a Jupyter notebook and a board-level presentation in the same week Communication: Ability to present complex AI and data concepts to executive stakeholders in a clear, concise fashion Proactive Problem-Solving: You don't wait for a tool to exist — you build it Adaptability Curiosity: Genuine enthusiasm for staying current with the rapidly evolving AI landscape Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-re ... (truncated, view full listing at source)