Sr. Director, Field Technology and AI

As the Sr. Director, Field Technology and AI, you will lead the GTM Technology organization responsible for accelerating and applying AI across Elastic's Go-to-Market motion. Reporting into Revenue Operations leadership, you will own the strategy, roadmap, and execution for four interconnected teams: Engineering, Data Science, Customer Data Strategy, and Application Administration. Together these teams form the engine for AI-driven GTM transformation at Elastic.

• Define and own the strategy for how Elastic applies AI across the GTM ecosystem, aligning Engineering, Data Science, Customer Data Strategy, and Application Administration into a unified roadmap that aligns with RevOps and GTM strategic priorities.
• Build, mentor, and lead an organization across four functional teams, each with their own leaders, roadmaps, and outcomes.
• Partner with senior GTM, Sales, Marketing, legal, IT, and Finance leaders to identify the highest-leverage GTM problems AI can solve, and lead those solutions from concept to adoption.
• Establish KPIs for AI-driven outcomes, system performance, data quality, and team delivery. Regularly report progress, trade-offs, and business impact to executive stakeholders.
• Serve as the senior technology voice within RevOps, translating GTM strategy into a technology agenda, and translating technology capability into GTM opportunity.
• Manage Engineering, Data Science, Customer Data Strategy, and Application Administration through their respective leaders.
• Drive alignment and shared outcomes with peer leaders across Revenue Strategy, Marketing, Finance, and IT.
• Champion a portfolio of applied AI use cases, including account scoring, next-best-action, seller copilots, agentic workflows, and conversational analytics, and drive each from design, prototype, and ultimately to scaled adoption.
• Make principled build/buy/partner decisions across the GTM tech stack, balancing innovation speed with platform stability, cost, and long-term scalability.
• Establish the principles, guardrails, and review mechanisms that ensure AI is deployed at Elastic in ways that are accurate, explainable, secure, and aligned with company values.

• 12+ years of progressive experience in GTM technology, RevOps systems, data/analytics, or applied AI, including 7+ years in senior leadership roles managing multiple sub-functions and leaders-of-leaders.
• Proven track record building or transforming a Field/GTM Technology organization in a global B2B SaaS environment, with measurable impact on pipeline, productivity, or revenue outcomes.
• Demonstrated success leading multi-disciplinary teams across engineering, data science, data strategy, and application administration, and creating an operating model that aligns them around shared outcomes.
• Exceptional executive presence and communication skills, with the ability to influence senior GTM, Marketing, Finance, and IT stakeholders, and to translate technical strategy into business outcomes.
• Track record of building, developing, and retaining strong technical leaders and specialized individual contributors.
• Deep fluency in the modern GTM technology stack, including CRM (Salesforce), marketing automation, sales engagement, CPQ, and the integration patterns that connect them.
• Strong working knowledge of modern data and AI stacks (BigQuery, Snowflake, Databricks, dbt, vector databases, LLM orchestration frameworks) and how they combine to deliver applied AI capabilities into operational workflows.
• Experience operationalizing ML and GenAI use cases inside GTM systems, moving from model output to embedded, adopted, measurable seller and leader experiences.
• Strong understanding of data governance, MDM, and the data quality foundation required to make AI trustworthy at enterprise scale.
• Sound judgment on engineering practices, system architecture, vendor selection, and total-cost-of-ownership trade-offs.

• Hands-on experience deploying agentic AI, retrieval-augmented generation (RAG), or knowledge-graph-based approaches in a GTM or enterprise operations context.
• Working knowledge of the Elastic Stack (Elasticsearch, Kibana, vector search) and how it can be leveraged to power internal GTM applications and AI use cases.
• Experience partnering closely with central IT/Enterprise Data organizations to deliver shared outcomes across organizational seams.

Compensation for this role is in the form of base salary. This role does not have a variable compensation component. The typical starting salary range for new hires in this role is $212,100—$335,600 USD. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range of $254,900—$403,200 USD may apply. In addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. The total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being.