Software Engineer, Native Learning Experiences
Remote • San Francisco • FullTime
Posted 10d ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
We are seeking a full-stack engineer to define and build a new category of learning experiences focused on AI education. This is an early-stage product area where strong technical judgment, product sense, and empathy for learners are crucial. You will be instrumental in setting the technical direction for how individuals learn to use AI safely and effectively. This hands-on role involves broad technical and product ownership, from initial concept through launch and iteration, shaping the future of how people learn at work.
Responsibilities
- Own the vision and execution for OpenAI's native learning offering.
- Build and launch end-to-end product experiences that help users build and apply AI skills through real work, starting in ChatGPT.
- Design core systems for learner state, progress tracking, content integration, experimentation, telemetry, and evaluation.
- Create reusable components and internal tools for education and content partners.
- Build and test clear entry points, hands-on practice, and feedback mechanisms, using data to inform future development.
- Partner closely with cross-functional teams including Customer Readiness, EDU Engineering, learning science, research, design, data, content, support, and customer-facing teams.
- Translate product and learning goals into requirements, prototypes, and product metrics in collaboration with design and users.
- Define learner intent and evaluate product quality, learning outcomes, and adoption against those goals using data and feedback.
- Make pragmatic tradeoffs in a 0-to-1 product area balancing speed, quality, scalability, and operational simplicity.
Requirements
- Substantial experience building and operating high-quality user-facing products with a record of staff-level technical leadership and hands-on delivery.
- Strong full-stack engineering skills, including modern frontend technologies (e.g., TypeScript, React), backend services and APIs, relational databases, stateful user flows, and instrumentation.
- Practical judgment regarding distributed systems, reliability, and performance.
- Experience building in 0-to-1 or fast-moving product environments where user needs and success measures are evolving.
- Strong user empathy and a high bar for product and interaction quality, accessibility, reliability, safety, security, and performance.
- Experience collaborating across engineering, research, product, design, data, content, operations, and customer-facing teams.
- Ability to use qualitative feedback and product data to identify friction and prioritize work.
- Clear written and verbal communication skills, including explaining technical decisions to diverse audiences.
- Careful judgment when building products that shape how people understand and use AI.