Fullstack Product Engineer (Learn & Agents)
About Sana
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.
If that’s a mission that excites you, you’re in the right place.
About the role
You will help build Sana’s core product experiences across both Agents and Learn, shipping customer-facing value quickly in small, high-ownership teams. You will work end to end, from clarifying problems with PM and Design to implementing delightful UX, robust APIs, and trustworthy instrumentation. Your focus will be on:
Creating powerful agentic workflows that help teams automate work and access knowledge.
Building world-class learning experiences that make it easy for people to learn anything with AI.
Integrating the two product pillars so that Sana’s agents and learning products feel like one coherent, magical experience.
You will own features from problem definition through design, implementation, launch, and iteration, always aiming to move the needle for Sana and our customers.
In this role, you will
Own features from design to deploy across the stack: frontend (React and TypeScript), backend (Node and TypeScript), and database (Postgres).
Build and evolve user experiences for Sana Agents, including chat interfaces, workflow builders, and tools that help customers orchestrate complex agentic flows.
Craft rich learning experiences in Sana Learn, such as interactive courses, knowledge experiences, and AI-assisted creation tools.
Integrate deeply with agent and retrieval APIs to deliver seamless, personalized product experiences across Agents and Learn.
Design and implement high quality APIs and data models that are shared across product surfaces, keeping Agents and Learn consistent and reliable.
Instrument product surfaces with analytics and logging so the team understands usage, quality, and performance.
Run A/B tests and other experiments to validate hypotheses and iterate quickly with Design and PM.
Make pragmatic trade-offs across scope, quality, and speed, especially in ambiguous 0 to 1 product spaces.
Collaborate closely with stakeholders, users, and teammates to discover the right problems to solve and to validate solutions early.
Work with infra, ML, and design partners to push what is possible with agentic AI in real customer workflows.
Help maintain a high engineering bar through code reviews, technical design discussions, and mentoring.
What success looks like
Features in Agents and Learn ship quickly, delight users, and drive measurable impact on key product and business metrics.
End to end ownership is the default: you pick up problems, shape them, ship them, and iterate based on data and feedback.
Product instrumentation and A/B tests consistently inform decisions and help the team learn what works.
You are a force multiplier for your squad, raising the bar for product thinking, technical quality, and collaboration.
Ambiguity around AI, agents, and new learning paradigms becomes an opportunity to innovate instead of a blocker.
Agents and Learn feel increasingly cohesive to customers: experiences are unified, reliable, and obviously powered by the same intelligent system.
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 infra: 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)
Sponsored
