About the company
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents.
Responsibilities
- Own the product roadmap and architecture direction for the Scaled Customer Enablement Agent Suite — defining the data inputs, retrieval sources, and agent behaviors that generate enablement recommendations.
- Lead the rollout and drive field adoption of the Scaled Customer Enablement Agent Suite, delivering automated learning insights and proposals to Account Teams.
- Structure the enablement knowledge base for retrieval — designing content schemas, metadata, and chunking so agents return accurate, grounded outputs — and maintain the underlying customer enablement playbook.
- Define the signals and triggers — usage patterns, learning milestones, and account-health thresholds — that prompt the agents to surface a free-to-paid enablement opportunity to Account Teams at the right moment.
- Partner with technical teams to embed enablement calls-to-action and insights directly into field tools.
- Define predictive signals and analytics that flag emerging account-health and skills gaps before they impact renewals or consumption, and integrate these into leadership reviews and manager coaching toolkits.
- Establish evaluation and quality loops for agent outputs — defining what “good” looks like, measuring accuracy and groundedness, and driving iteration with the technical team.
Requirements
- 6+ years of experience in Sales Enablement, GTM Program Management, or Sales Operations in a high-growth SaaS environment.
- Proven track record of managing complex workstreams and delivering global field motions with measurable adoption.
- Hands-on fluency with modern AI systems — RAG pipelines, agents, and LLM-powered workflows. You understand how retrieval sources, prompt design, context and data hierarchies, and grounding affect output quality, and can translate that into requirements a technical team can build against.
- Demonstrated experience owning a product or system area end to end — defining requirements, collaborating with engineering and data teams, and shipping AI-powered capabilities from concept to field adoption.
- Comfort defining metrics and running experiments — instrumenting agent performance, measuring output quality and field adoption, and using analytics to drive iteration.
- Exceptional ability to work cross-functionally across Sales, Marketing, and Technical teams to ensure a unified enablement vision.
- Expert at using data dashboards to track progress and communicate the "business story" behind the numbers (e.g., the link between enabled users and consumption lift).
- Able to solve ambiguous problems in a fast-moving environment and translate complex strategies into simple, executable field instructions.
- Familiarity with the education technology or customer training landscape is a significant plus.
- Familiarity with how enablement and knowledge content must be structured for machine consumption (schemas, metadata, modularity) is a strong plus.