Sr. Director, Field Technology and AI

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

What is The Role

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.

This is a senior, enterprise-wide leadership role with a strong team and clear direction. Data Science creates new synthetic signals for action. Customer Data Strategy ensures the underlying data is certified and trustworthy for all teams. The Field Engineering team builds the systems that operationalize it inside GTM workflows. Application Administration sustains the platforms where it all comes to life. Your responsibility is to align these disciplines into a single, coherent operating model that solves GTM problems at scale. You will set the vision for how AI is embedded into the seller and GTM leader experience, while ensuring each team delivers against its own roadmap, outcomes, and success measures in service of broader fiscal-year strategic goals.

What You Will Be Doing

• Strategy & Leadership
  
  
  
  • Set the Field Technology & AI Vision: 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.
  
  
  • Lead a Multi-Disciplinary Organization: Build, mentor, and lead an organization o across four functional teams, each with their own leaders, roadmaps, and outcomes. Set clear success measures, develop leaders, and create the framework for success
  
  
  • Drive AI Adoption Across GTM: 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.
  
  
  • Measure & Communicate Impact: Establish KPIs for AI-driven outcomes, system performance, data quality, and team delivery. Regularly report progress, trade-offs, and business impact to executive stakeholders.
  
  
  • Operate as an Executive Partner: Serve as the senior technology voice within RevOps, translating GTM strategy into a technology agenda, and translating technology capability into GTM opportunity.
  
  
  
  

• Execution & Delivery
  
  
  
  • Lead Four Functional Teams: Manage Engineering, Data Science, Customer Data Strategy, and Application Administration through their respective leaders. Set distinct roadmaps, success measures, and operating cadences for each team while ensuring their outputs combine into a single, coherent GTM technology portfolio.
  
  
  • Influence Beyond Your Org: Drive alignment and shared outcomes with peer leaders across Revenue Strategy, Marketing, Finance, and IT. Shape executive-level decisions on GTM priorities, secure cross-functional investment in your roadmap, and resolve trade-offs that span organizational boundaries.
  
  
  • Productize AI for GTM: 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.
  
  
  • Govern the Technology Portfolio: Make principled build/buy/partner decisions across the GTM tech stack, balancing innovation speed with platform stability, cost, and long-term scalability.
  
  
  • Embed AI Responsibly: 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.
  
  
  
  

What You Bring

• Strategic Leadership & GTM Understanding
  
  
  
  • 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.
  
  
  
  

• Technical Expertise & Execution
  
  
  
  • 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.
  
  
  
  

Bonus Points

• 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.