Senior Backend Engineer

Sana is an AI lab building superintelligence for work.

We believe organizations can accomplish their missions faster when humans can effortlessly access knowledge, automate repetitive work, and learn anything with the help of agentic AI.

As part of Workday, we are committed to building AI that augments humans.

If that's a mission that excites you, you're in the right place.

This role focuses on building and scaling Sana's search infrastructure (with emphasis on retrieval systems, ranking algorithms, and search APIs) to handle enterprise-scale knowledge discovery. The main responsibility is to architect search systems that handle 10-100x current volumes while maintaining sub-second latency and exceptional relevance. Strong expertise in Vespa or similar search engines, vector databases, and embedding models is essential for success in this role. Agents are bottlenecked by what they know, and search is the key piece to enable agents to reason and act on relevant context. This means that we need to reconsider the search stack for the era of agents.

You'll be joining a talented engineering team where you'll collaborate closely with backend, search, AI, and infrastructure engineers to shape our search architecture—this is not a solo mission, but a collective effort to reimagine knowledge discovery.

• Architect and scale our search infrastructure to handle billions of documents while maintaining sub-second response times across complex multi-tenant environments

• Design hybrid search systems that seamlessly blend traditional keyword search with semantic understanding, leveraging state-of-the-art vector databases and retrieval models

• Build intelligent ranking and personalization systems that learn from user behavior to improve relevance continuously

• Collaborate with our AI engineers to integrate large language models into the search pipeline, creating retrieval-augmented generation systems that transform how people interact with knowledge

• Optimize search performance across the stack—from query parsing and index design to distributed system architecture

• Lead the development of our search observability and quality frameworks, establishing metrics and systems to measure and improve search relevance

• Work closely with product and design to shape the future of knowledge discovery at Sana

• Build search systems that scale elegantly—architecting for billions of documents and millions of queries while meeting strict latency requirements.

• Design search systems that apply proven, scalable techniques as well as latest practical advancements in semantic AI retrieval

• Proactively identify search quality issues through comprehensive observability—establishing metrics, monitoring, and automated quality regression detection

• Balance hands-on implementation with system design, mentoring team members on search best practices and IR fundamentals

• Apply deep search infrastructure expertise (index optimization, query planning, distributed retrieval, caching strategies) to solve performance bottlenecks before they impact users

• Drive the evolution from traditional search to AI-powered discovery, integrating embedding models, reranking systems, and RAG pipelines while maintaining system reliability

• Ensure our search infrastructure can handle enterprise-scale deployments with strict latency SLAs, multi-tenancy isolation, and 99.99% uptime

• Help shape AI's future alongside brilliant minds from Notion, Dropbox, Slack, Databricks, Google, McKinsey, and BCG.

• Competitive salary complemented with a transparent and highly competitive options program.

• Swift professional growth in an evolving environment, supported by a culture of continuous feedback and mentorship from senior leaders.

• Work with talented teammates across 5+ countries, and collaborate with customers globally

• Regular team gatherings and events (recently in Italy and South Africa)