Staff Software Engineer - Frontend (NYC)

• Create novel, never-seen-before interfaces for GenAI agents that manage complex workflows while keeping the human in the loop through inspectability and transparency
• Partner closely with product management, design and other engineering teams to build intuitive and extensible products that drive user & business growth
• Lead by example with hands-on front-end and full-stack software development while working with customers directly to create dynamic, user-centric experiences
• Enable mechanisms that can drive product-led growth, through seamless onboarding and sharing capabilities
• Direct the future of intuitive agentic applications at Databricks, in collaboration with cross-functional teams of innovative software engineers, product managers, and designers

Do you have experience in Vue.js?, * 10 years of experience with HTML, CSS, and JavaScript or similar technologies

• Demonstrated product mindset with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback.
• You care that AI features feel intuitive, trustworthy, and helpful, not just bolted on to an existing app
• High ownership and bias for action in 0 1 environments: you are comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption.
• Strong ability to collaborate across product, engineering, and design teams to align technical strategy with company growth objectives.
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember)
• Familiarity with server-side web technologies (eg Node.js or similar), SQL and Spark

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

Local Pay Range $190,900-$253,750 USD, At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.

At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best Data Intelligence Platform so our customers can use deep data insights to improve their business. Founded by engineers - and customer obsessed - we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we’re only getting started.

As one of the first engineers in the NYC Engineering office, you’ll have the opportunity to be part of a small, nimble team that’s innovating to build new products from the ground up. Our goal is to leverage the power of Databricks in data & AI to deliver vertical AI applications for both technical and business users. This will be a true 0-to-1 environment, combining the excitement of a startup with the resources of a tech leader like Databricks., Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.