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 and AI infrastructure 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.

Our Vector Search technology is at the heart of this mission, enabling developers to build a wide spectrum of AI applications — from Retrieval-Augmented Generation (RAG) and recommendations to matching systems and product search experiences. It supports scalable similarity search across diverse datasets, including structured, semi-structured, and unstructured content such as PDFs, Office documents, and wikis. This flexibility has made Vector Search our fastest-growing product, fueled by the rapid adoption of Generative AI across industries.

As a Staff Engineer, you’ll play a key role in scaling the foundation of our Vector Search product by designing and evolving distributed systems that serve as the backbone of real-time, AI-powered applications. You’ll lead complex design and implementation efforts, shape the evolution of distributed systems that power AI applications, and contribute to architectural decisions that ensure high performance, scalability, and reliability. Beyond hands-on contributions, you’ll help define the long-term vision, mentor senior engineers, collaborate with cross-functional stakeholders, and lead strategic efforts that create outsized technical and business impact.

The impact you will have:

• Lead design and implementation of critical components of the Vector Search engine that enable scalable, low-latency search and retrieval across large, multimodal datasets.
• Solve complex technical challenges in areas like indexing, ranking, query execution, and storage — blending traditional information retrieval and modern vector search techniques.
• Collaborate with infrastructure, product, and research teams to define APIs and developer workflows that simplify building production-grade AI applications.
• Deliver high-quality, production-ready code and services end-to-end — including performance tuning, resiliency improvements, and debugging in live environments.
• Help raise the engineering bar through code reviews, design discussions, and mentorship.
• Contribute to longer-term technical planning and support strategic initiatives in search infrastructure and AI systems.

What we look for:

• 10+ years of industry experience building and operating large-scale distributed systems.
• Expertise in Search Engines (vector and/or keyword-based), including areas such as indexing, ranking, retrieval infrastructure, and query execution.
• Familiarity with storage systems and database internals.
• Strong foundation in algorithms, data structures, and system design, especially as applied to real-world data processing and retrieval problems.
• Track record of driving high-impact, technically complex initiatives that delivered clear customer or business value.
• Experience leading architecture efforts for performance-sensitive systems (e.g., latency-critical services, multi-tenant platforms, large-scale indexing pipelines).
• Strong communication skills and comfort operating in fast-moving, cross-functional environments.
• A strategic mindset with the ability to align engineering execution with longer-term product and company goals.
• Passion for mentoring and developing other engineers.