Main Responsibility

Platform evangelism & community
Champion Databricks capabilities (Agent Bricks, Genie Spaces, Unity Catalog, Feature Store) across all data science teams
Organize and deliver internal community trainings and hands-on workshops
Build and nurture a community of practice around AI/ML, acting as a credible technical reference
Present at internal tech forums and represent the platform vision to senior leadership

Standards & frameworks
Define group-wide guidelines for when and how to apply generative AI vs traditional ML approaches
Establish MLOps and AI Ops standards covering model lifecycle, monitoring, governance, and deployment patterns
Create decision frameworks to help teams choose the right tools and architectures for their use cases
Drive adoption of responsible AI principles and data governance best practices

Documentation & blueprints
Produce high-quality technical blueprints, reference architectures, and step-by-step implementation guides
Write opinionated best-practice guides that balance technical rigour with practical usability
Translate complex platform updates into accessible, well-structured internal communications

Platform feedback loop
Collect pain points and adoption blockers from teams and feed them back to platform owners
Evaluate new features and GenAI tooling, producing adoption recommendations
Act as a bridge between the platform team and the data science community

Soft Skills & Profile
Communication & influence
Exceptional ability to explain complex technical concepts to both technical and non-technical audiences
Confident and engaging presenter and trainer, able to inspire, not just instruct

Leadership & collaboration
Comfortable operating as a senior individual contributor and internal thought leader
Highly collaborative, builds trust with data scientists, engineers, and business stakeholders alike
This is a non-people-management, group-wide role, ideal for someone wanting to grow as an AI reference within an enterprise environment. Experience & Seniority
3+ years of experience in data science, ML engineering, or AI platform roles
Demonstrated hands-on expertise with Databricks in a production environment
Proven track record of driving technology adoption at scale and enablement experience is a strong plus
Experience defining MLOps or AI Ops practices across multiple teams or business units