As noted above, this list is intended to reflect the current job but there may be additional essential functions (and certainly non-essential job functions) that are not referenced. Management will modify the job or require other tasks be performed whenever it is deemed appropriate to do so, observing, of course, any legal obligations including any collective bargaining obligations.
Responsibilities include the following:
- Design, build, and deploy AI agents and models on Databricks and Microsoft Copilot/Fabric, leveraging tools such as Genie Spaces, Agent Bricks, and LLM-based workflows to automate and enhance intelligence for Global Sales.
- Develop and maintain AI governance frameworks — including model documentation, performance monitoring, lineage tracking, and compliance standards — to ensure responsible and auditable use of AI across sales programs.
- Build and optimize data pipelines supporting AI/ML workloads within a medallion architecture on Azure Databricks (Delta Lake, Unity Catalog), with integration into Microsoft Fabric and OneLake for downstream consumption.
- Innovate on emerging Databricks and Microsoft Fabric capabilities as they are released, rapidly evaluating and prototyping features that can strengthen the team’s technical foundation and revenue impact.
- Collaborate with business stakeholders in Global Sales to understand operational challenges and translate them into AI-driven solutions, communicating findings and recommendations clearly to both technical and non-technical audiences.
- Create AI-powered reporting and analytical models within Genie Spaces, Databricks Apps, and Power BI Direct Lake semantic models that empower sales leaders to understand program performance, identify opportunities, and act with confidence.
- Champion continuous improvement by staying current with advancements in generative AI, agentic frameworks, and large language model tooling, bringing a mindset of experimentation and responsible innovation to the team.
- Support the full AI development lifecycle — from ideation and prototyping through production deployment and ongoing monitoring — in close partnership with data engineering and Sales IT teams.