Software Engineer, Native Learning Experiences

About the Team Customer Readiness helps customers and partners build the practical skills and confidence to use AI and OpenAI products safely and effectively. The team focuses on role- and skill-based learning paths, practical content, and product experiences that accelerate learning in the workplace. It brings together learning and enablement expertise, field insight, product signals, and measurement to improve learner and business outcomes. Together, these experiences will help enterprise users build practical AI skills, apply them with confidence in their work, and demonstrate what they can do. Employers will gain a clearer view of workforce skills and progress, helping them recognize capability, focus development where it matters most, and build confidence in workforce readiness. About the Role We’re looking for a full-stack engineer to define and build a new class of learning experiences. This is an early-stage product area where technical judgment, product sense, and learner empathy are critical. You will be setting a technical vision for how people use AI to learn how to use AI, safely and beneficially. This is a hands-on, 0-1 product engineering role with broad technical and product ownership. You’ll set direction, make foundational decisions, and ship the first versions of experiences that can grow into the default way people learn at work. You will drive full-stack product experiences end to end, from prototype through launch, instrumentation, iteration, and production hardening. The work spans interaction design, frontend implementation, backend APIs and services, learner state, content and runtime integration, telemetry, evaluation, reliability, safety, accessibility, and launch readiness. You’ll work closely with our education, GTM, and engineering teams to translate how people learn into products people want to use. bring role- and skill-based learning paths into the product, designing coaching, feedback, and adaptive support which responds to each learner’s goals, context, and progress. You’ll lead focused experiments, measure what helps learners progress and where they struggle, and use that evidence to shape what comes next. Strong candidates will be product engineers with experience and a strong interest in education, learning science, assessment, behavior change, or AI literacy. You’ll help shape how OpenAI supports structured, adaptive learning in the flow of work, from a learner’s first entry point through practice, feedback, progress, and repeated use. In this role, you will: Own the vision and execution for OAI’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 the core systems behind those experiences, including learner state, progress and re-entry, content and runtime integration, experimentation, telemetry, and evaluation Create reusable components and internal tools that allow education and content partners to develop, configure, test, and improve learning experiences Build and test clear entry points, realistic hands-on practice, useful feedback, telemetry, and evaluation. Use evidence from real use to decide which capabilities for saved context, progress, re-entry, and reuse are needed next. Partner closely with colleagues across Customer Readiness, EDU Engineering, learning science, research, design, data, content, support, and customer-facing teams. Reuse technical and learning patterns where they help while keeping the experience grounded in professional and enterprise use cases. Work closely with design and users to turn product and learning goals into clear requirements, prototypes, milestones, reusable UI patterns, and product metrics, then refine the experience through evidence. Define the learner intent and problem for each release, then use product data, learner feedback, and operational signals to evaluate product quality, learning, transfer to real work, and adoption against that intent. Make pragmatic tradeoffs across speed, quality, scalability, and operational simplicity in a 0-to-1 product area. Qualifications: 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 such as TypeScript and React, backend services and APIs, relational databases, stateful user flows, and instrumentation, with practical judgment about distributed systems, reliability, and performance. Experience building in 0-to-1 or fast-moving product environments where user needs, product shape, and success measures are still 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