OpenAI의 GTM Growth Engineering 팀에서 사용자의 AI 학습 경험을 설계할 풀스택 엔지니어를 찾습니다. 4년 이상의 경력을 바탕으로 제품의 0-to-1 과정을 주도하며, 사용자 온보딩 및 학습 흐름을 구축합니다. 제품 판단력과 풀스택 기술 역량을 통해 AI 리터러시를 높이고 비즈니스 성과를 창출하는 것이 핵심입니다.
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.
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.
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.
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 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.
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, experimentation, evaluations, or learning measurement.
Experience building product surfaces used by both individual users and organizations, including admin, reporting, or support-readiness considerations.
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
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Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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