
Associate I, Business Operations
Databricks · Chicago, Illinois
Job description
SLSQ427R538 The impact you will have: Databricks' Sales Operations team is transforming how operational work gets done. We are shifting from manual, high-volume request processing to an AI-first operating model — where AI agents handle repeatable work autonomously and the team focuses on building, governing, and improving those systems. This role is central to that transformation. You will own a portfolio of AI agent workflows that automate business-critical Sales Operations processes. You translate business requirements into agent designs, deploy them into production, monitor performance, and continuously improve them. You also lead systems improvement projects — diagnosing integration issues, fixing data quality problems, and coordinating solutions across platforms. This is a cross-functional role partnering with Strategy, Planning, Finance, IT, and Data Engineering teams across our enterprise systems stack. Build and operate AI agents — translate operational SOPs into agent workflows; deploy, monitor, and fine tune agents that handle field requests autonomously Own an agent portfolio — manage a set of automated workflows end-to-end, including agent-to-human escalation paths and performance optimization Drive process and systems improvement — identify next workflows to automate; diagnose cross-system integration issues; lead data quality remediation Partner cross-functionally — gather requirements from Sales, Finance, IT, and Strategy stakeholders; influence Directors and Sr. Directors on automation priorities Support operational continuity — contribute to critical business processes including annual planning cycles What we look for: 5–8 years in operations, systems administration, or business process automation — ideally in high-growth tech companies Systems fluency — understands APIs, data schemas, and integration patterns; knows how enterprise systems connect AI-native thinking — uses LLMs, agent platforms, and automation tools to solve business problems; strong judgment on when to automate vs. when manual oversight is needed AI agent deployment — hands-on experience
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