Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data + AI Platform. Backed by Battery, Insight and Kleiner Perkins.
About the role
You'll design for two audiences at once: an open-source community shaping the future of agent workflows, and enterprise teams adopting agents in governed production. You'll be the IC design lead for how humans and fleets of agents work together on Omnigent - leading through product strategy, systems thinking, craft, and cross-functional collaboration. You're equally comfortable shipping small design changes directly in the codebase and prototyping your way through big, ambiguous problems that don't have a spec yet. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- A portfolio of strong end-to-end craft - interaction design, visual/UI polish, and design-systems thinking - ideally on developer tools, AI/ML products, enterprise software, or other products for technical users
- Staff-level scope and impact. A track record of shipping complex, high-quality developer products and leading design direction on hard problems
- Self-directed, and comfortable in ambiguity - you help shape product direction when the path isn't defined
- A strong collaborator who raises the level of high-quality critique, clear decision-making, and tight partnership with engineering and product
More about this role
RDQ427R613
Databricks is the Data and AI company. More than 10,000 organizations worldwide rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. As agents move from demos to real production work, Databricks is building the platform that lets enterprises create, govern, and collaborate with coding agents safely and at scale.
Omnigent is Databricks' platform for building, composing, governing, and sharing AI coding agents. It lets people create and coordinate agents across different model providers and execution environments - from the CLI and IDE to desktop, mobile, and managed enterprise surfaces. Users can watch agents work live, jump in to co-drive or fork a session, and package and share reusable agents.
This is a rare chance to define and refine interaction patterns at enterprise scale: how people supervise fleets of agents, intervene at the right moment, understand risk, and build trust in autonomous work - starting with coding, review, and exploration workflows. The hard design problem isn't just showing what agents are doing; it's helping people know when to trust, when to step in, and how to recover when work goes off track -...
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