About the job
Join Our Team at Sana
Sana is an innovative AI laboratory dedicated to creating superintelligent solutions for enhancing workplace productivity. We believe that organizations can achieve their goals more efficiently when teams access knowledge seamlessly, automate mundane tasks, and leverage the power of agentic AI for continuous learning. As a proud member of Workday, we are on a mission to develop AI that complements human capabilities rather than replacing them.
Our vision is brought to life through our two flagship products. Sana Agents streamline access to your organization’s applications, knowledge, and data, allowing AI agents to perform meaningful work and enabling teams to process and act on information at an unparalleled scale. Sana Learn serves as an AI-driven learning platform, blending the ease of a modern educational tool with intelligent features like AI tutoring, automated content creation, and interactive applications, ensuring knowledge is not only accessible but also actionable.
Our team is composed of highly skilled engineers and designers from top-tier companies such as Google, Spotify, Apple, and Databricks, all driven by a shared commitment to technical excellence and rapid iteration. Our tools currently empower over a million users to enhance their learning and work processes across hundreds of leading enterprises, and we are just getting started.
About the Role
You will play a pivotal role in developing and optimizing the core backend systems that support Sana’s Learn platform and search infrastructure. Your mission will be to redesign and scale these systems to efficiently handle enterprise-level workloads, eliminate bottlenecks, and evolve our architecture to meet the demands of the AI era.
Responsibilities
- Transform existing components to accommodate enterprise-scale workloads.
- Identify and address bottlenecks in storage, query performance, APIs, and data models.
- Lead the transition from outdated systems to sustainable, modern solutions.
- Enhance the reliability and efficiency of APIs.
