Product Engineer, Growth & AI Learning Experiences

About the team GTM Growth Engineering builds product systems that help OpenAI's go-to-market organization scale with better signal, faster learning, and more leverage. We work in live GTM workflows where agents and humans together identify important customer moments, recommend or take the next action, route judgment-heavy work, and measure whether the workflow improved business outcomes. The Learning Experiences pod sits inside GTM Growth Engineering. Its focus is helping users and organizations build practical AI literacy and confidence inside OpenAI products: contextual guidance, hands-on practice, feedback, progress, re-entry, and clear next steps. About the role We're looking for a product engineer to help build learning experiences directly inside OpenAI products that drive user acquisition, activation, retention, and more meaningful use of AI. You will turn ambiguous product and learning goals into polished, reliable, user-facing experiences that help people learn by doing. You will own meaningful product slices end to end: interaction design details, frontend implementation, backend APIs and services, progress/state, content and runtime integration, telemetry, and launch readiness. The role is ideal for a strong product engineer who can connect product craft to measurable outcomes, with an added spike in education, learning science, coaching, assessment, onboarding, training, enablement, or AI literacy. What You'll Do - Build end-to-end product experiences that help users learn AI through real tasks inside OpenAI products. - Own full-stack product slices from prototype through launch, hardening, instrumentation, and iteration. - Create intuitive flows for onboarding, guided modules, practice, knowledge checks, feedback, progress, re-entry, and recommended next steps. - Build product flows that respond to a user's starting point and avoid one-size-fits-all learning paths. - Partner with product, design, content, research, data, customer-facing, safety, privacy, support, and go-to-market teams to ship trustworthy learning experiences. - Turn learning goals into clear product flows, reusable UI patterns, and product metrics we can improve. - Instrument the experience so we can understand usage, friction, completion, learning signals, and product quality. - Connect learning experiences to real product usage, user feedback, and operational signals so the product improves as it scales. - Make pragmatic tradeoffs across speed, quality, scalability, and operational simplicity in a 0-to-1 product area. What We're Looking For - Have 4+ years of experience as a software, product, or full-stack engineer building high-quality user-facing products. - Strong product judgment and a track record of turning ambiguous ideas into shipped product. - Strong frontend or full-stack engineering skills, with comfort across modern web apps, APIs, data models, stateful user flows, and instrumentation. - Experience building in 0-to-1 or fast-moving product environments where user needs, product shape, and success metrics are still being discovered. - A high bar for UX quality, interaction details, accessibility, reliability, and user empathy. - Experience partnering closely with design, product, research, data, content, operations, and customer-facing stakeholders. - Ability to use qualitative feedback and product data to identify friction, prioritize work, and improve outcomes. - Clear written and verbal communication, especially when simplifying complex technical concepts for different audiences. - Careful judgment when building products that shape how users understand and use AI. You Might Thrive If - You like 0-to-1 product work where the right answer is discovered through shipping, measurement, and iteration. - You are excited by product surfaces that sit close to real users, real workflows, and measurable business outcomes. - You can move between prototype speed and production-quality engineering without losing sight of the user. - You enjoy working with non-engineering partners and turning domain expertise into clear product experiences. - You are energized by education, behavior change, skill development, or helping people gain confidence with new tools. - You have strong opinions about product craft but can adjust quickly as evidence comes in. Nice to Have - Experience building education, edtech, learning, tutoring, coaching, assessment, onboarding, training, or enablement products. - Experience in AI literacy, workforce learning, enterprise enablement, developer education, or similar spaces where users need to build confidence and skill over time. - Experience building AI products, LLM applications, developer tools, agent-assisted workflows, or personalized user experiences. - Experience building customer-facing, revenue, sales, support, or go-to-market systems where product quality and operational feedback loops matter. - Experience with feedback loops, diagnostics, telemetry, experimenta

4+ years of experience as a software, product, or full-stack engineer building high-quality user-facing products. Strong product judgment and a track record of turning ambiguous ideas into shipped product. Strong frontend or full-stack engineering skills, with comfort across modern web apps, APIs, data models, stateful user flows, and instrumentation. Experience building in 0-to-1 or fast-moving product environments where user needs, product shape, and success metrics are still being discovered. A high bar for UX quality, interaction details, accessibility, reliability, and user empathy. Experience partnering closely with design, product, research, data, content, operations, and customer-facing stakeholders. Ability to use qualitative feedback and product data to identify friction, prioritize work, and improve outcomes. Clear written and verbal communication, especially when simplifying complex technical concepts for different audiences. Careful judgment when building products that shape how users understand and use AI.

Build end-to-end product experiences that help users learn AI through real tasks inside OpenAI products. Own full-stack product slices from prototype through launch, hardening, instrumentation, and iteration. Create intuitive flows for onboarding, guided modules, practice, knowledge checks, feedback, progress, re-entry, and recommended next steps. Build product flows that respond to a user's starting point and avoid one-size-fits-all learning paths. Partner with product, design, content, research, data, customer-facing, safety, privacy, support, and go-to-market teams to ship trustworthy learning experiences. Turn learning goals into clear product flows, reusable UI patterns, and product metrics we can improve. Instrument the experience so we can understand usage, friction, completion, learning signals, and product quality. Connect learning experiences to real product usage, user feedback, and operational signals so the product improves as it scales. Make pragmatic tradeoffs across speed, quality, scalability, and operational simplicity in a 0-to-1 product area.