Sana is an AI lab building superintelligence for work. We believe organizations can accomplish their missions faster when teams 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 people - not replaces them.
We bring this mission to life through two products. Sana Agents provide a seamless way to access all your company’s apps, knowledge, and data, enabling AI agents to do real work so teams can process and act on information at unprecedented scale. Sana Learn is an AI-powered learning hub that combines the simplicity of a modern learning platform with intelligent features like an AI tutor, automated content generation, and interactive apps, making knowledge not just accessible but actionable.
We’re a talent-dense, product-obsessed team of engineers and designers from companies like Google, Spotify, Apple, and Databricks, united by deep technical excellence and rapid iteration. Our tools already help over a million people learn and work better across hundreds of leading enterprises - and we’re just getting started.
You will work on the core backend systems that power Sana’s Learn platform and search infrastructure. You will redesign and scale systems to handle enterprise workloads, remove deep bottlenecks, and evolve our architecture for the era of AI and agents.
We are hiring for two senior roles:
Senior Backend Engineer, Learn (Core Systems)
Senior Backend Engineer, Search
You will focus on making the Learn platform, especially Manage, Insights, and APIs, scalable and maintainable for enterprise use. You will take systems that work at current scale and redesign them to handle much larger volumes of data, users, and entities. The work is primarily architectural and system level, with strong emphasis on Postgres and database design.
Redesign existing components to support enterprise scale workloads
Analyze and resolve bottlenecks in storage, query performance, APIs, and data models
Lead migrations away from legacy implementations to sustainable replacements
Improve reliability and efficiency of APIs and integrations for internal and external clients
Drive technical projects from definition to delivery with Product Managers and other teams
Maintain a long term view of system health and architecture
Share technical knowledge, review designs, and set best practices for backend and systems design
Architecture and scalability are prioritized over short term fixes
Risks are identified early and addressed with solid technical solutions
You balance hands on coding with architectural leadership
Learn core systems support larger enterprise customers without performance or reliability issues
Strong Postgres skills (schema design, query optimization, indexing) improve performance and scalability
You will build and scale Sana’s search infrastructure for enterprise scale knowledge discovery. You will architect retrieval systems, ranking algorithms, and search APIs that handle large increases in volume while maintaining sub second latency and high relevance. You will rethink the search stack for the era of agents, using engines like Vespa, vector databases, and embedding models.
Architect and scale search infrastructure to billions of documents in multi tenant environments
Design hybrid search that combines keyword search with semantic understanding and vector search
Build ranking and personalization systems that learn from user behavior
Collaborate with AI engineers to integrate large language models into the search pipeline and build retrieval augmented systems
Optimize search performance across query parsing, index design, and distributed architecture
Lead development of search observability and quality frameworks with clear metrics and monitoring
Work closely with product and design to shape the future of knowledge discovery at Sana
Search systems scale elegantly to billions of documents and millions of queries with strict latency targets
Systems apply proven IR techniques and practical advances in semantic AI retrieval
Search quality issues are detected early through strong observability and automated regression checks
You balance implementation with system design and mentor others on search and IR fundamentals
Deep expertise in search infrastructure (index optimization, query planning, distributed retrieval, caching) prevents performance issues before users see them
The stack evolves from traditional search to AI powered discovery, including embeddings, reranking, and RAG, while staying reliable
Search infrastructure supports enterprise deployments with strict SLAs, multi tenancy isolation, and very high uptime
We build on a simple modern stack optimized for both humans and AI.
Backend: TypeScript, Kotlin, Node.js
Frontend: TypeScript, React, Tailwind
Databases: Postgres, Redis
Cloud infra: GCP/Kubernetes/Terraform
Help shape AI's future alongside brilliant minds from Google, Apple, Spotify, Notion, Slack, Databricks, 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 global customers, from our beautiful office in Stockholm.
Regular team gatherings and events (recently in Italy and South Africa)
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