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 feedback and product data to identify friction, prioritize work, and improve outcomes.
Clear written and verbal communication, including the ability to explain technical decisions and tradeoffs to different audiences.
Careful judgment when building products that shape how people understand and use AI.
You might thrive in this role 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 user and 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:
5+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies
Former founder, or early engineer at a startup who has built a product from scratch is a plus
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 translating research into product decisions, experiments, evaluation, measurement, and iteration.
Experience building product surfaces used by both individual users and organizations, including admin, reporting, or support-readiness considerations.
About OpenAI
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.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
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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