AI Engineer

About Sana

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 is a mission that excites you, you are in the right place.

About the roles

You will join the core team building the agent and search infrastructure that powers Sana’s mission to bring superintelligence to work. You will work at the intersection of agent architecture, context and tool engineering, search and retrieval, and production infrastructure, designing systems that reliably handle real-world enterprise complexity at scale.

We are hiring for two closely related roles:

• AI Engineer, Agents

• AI Engineer - Search, Agents

1. AI Engineer, Agents

What you will do

• Architect multi-step planning, orchestration, and tool routing for agents

• Implement code generation agents and sandboxed code execution

• Engineer memory, state, and context packing and grounding strategies

• Balance latency, quality, and cost controls for agent execution

• Develop safe fallbacks, graceful degradation, and robust error handling

• Collaborate with platform and search teams to deliver reusable agent infrastructure

• Establish safety guarantees and measurable quality improvements in agent behavior

What success looks like

• Agent architectures are robust, reliable, and ready for enterprise use

• Context and tool engineering enable agents to act intelligently at scale

• Clear metrics, automated evaluation, and continuous improvement in agent capabilities

• Quality and safety are measurable and improving over time

• Durable building blocks accelerate product teams and unlock new capabilities

2. AI Engineer - Search, Agents

What you will do

• Scale search infrastructure to billions of documents in multi-tenant environments

• Design hybrid retrieval that combines semantic vector search with traditional information retrieval techniques

• Build ranking systems that learn from user behavior to improve relevance

• Optimize the full search stack, including query understanding, indexing, and distributed retrieval

• Establish observability frameworks to measure and improve search quality

• Partner with product and design teams to shape the future of knowledge discovery for agents

What success looks like

• Search scales to enterprise volumes with sub-second latency and high availability

• Retrieval combines proven information retrieval techniques with modern agentic search

• Quality metrics and regression detection catch issues before they impact users

• You balance hands-on implementation with system design and mentorship

• Performance bottlenecks are identified and resolved proactively across the stack

• Agents consistently find and use the right context to serve users

Our tech stack

We build on a simple modern stack optimized for both humans and AI:

• Backend: TypeScript, Node.js

• Frontend: TypeScript, React, Tailwind

• Databases: Postgres, Redis

• Cloud infrastructure: GCP, Kubernetes, Terraform

What we offer

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

• Competitive salary and compensation package

• 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)