Full Stack Software Engineer, ChatGPT Finances

The ChatGPT Finances team builds experiences that help people connect their financial accounts, understand their financial picture, and ask useful questions about their finances through ChatGPT. Our work spans account connectivity, data ingestion, dashboards, personalized insights, and conversational experiences. We collaborate across product, design, research, infrastructure, security, and data integrations to make complex financial information understandable and actionable. This is an early and ambitious product area with a substantial roadmap. We are looking for engineers who want to shape both the first user experiences and the durable systems required to earn and keep users’ trust. About the role We’re looking for full-stack product engineers to build and scale ChatGPT Finances. You will own features across the stack—from polished frontend experiences to the APIs, services, and data models that power them. This role is well suited to engineers who combine strong product judgment with broad technical depth. You should care about how quickly users can understand their financial lives, how reliably data moves through the system, and how AI can answer financial questions in a grounded, transparent, and useful way. You will work closely with product, design, research, infrastructure, security, and data integration teams to take ideas from early prototypes to reliable production experiences. In this role, you will - Own full-stack product features from user experience and frontend implementation through backend services, data models, deployment, and observability. - Build polished, accessible, and performant interfaces for account connection, dashboards, insights, and conversational workflows. - Design APIs and backend systems that safely ingest, normalize, and serve financial data. - Build resilient integrations that handle synchronization, data freshness, partial failures, permissions, and user consent. - Bring new AI capabilities into production while prioritizing grounding, accuracy, transparency, and user control. - Establish architecture, performance standards, testing practices, and operational safeguards for a fast-growing product area. - Debug and improve complex behavior across client, server, infrastructure, and external integrations. - Use qualitative feedback, product metrics, and experiments to improve user outcomes without compromising clarity or trust. - Collaborate across disciplines to turn ambiguous product opportunities into simple, reliable experiences. You might thrive in this role if you - Have experience building and shipping full-stack consumer products in production. - Are comfortable working in a modern frontend stack and building the APIs and services behind it. - Care deeply about product craftsmanship, performance, accessibility, and details that affect the user experience. - Understand API design, data modeling, system reliability, and the tradeoffs involved in evolving production systems. - Can move effectively between frontend, backend, and product decisions rather than remaining in a narrow implementation area. - Have strong product judgment and can take a feature from a rough idea to a shipped, measurable outcome. - Work well in ambiguous, high-impact areas where the product and technical architecture are still taking shape. - Think carefully about privacy, security, reliability, and user trust when working with sensitive data. - Enjoy diagnosing problems across system boundaries and improving the underlying engineering foundations. - Are interested in AI-native interfaces and new ways to make complex personal information easier to understand. Preferred qualifications - Experience building backend services using languages and frameworks such as Python, Go, Node.js, or comparable technologies. - Experience with frontend development using React / Typescript, or Swift or Kotlin. - Experience operating consumer products or distributed systems at scale. - Experience with fintech, personal finance, banking, payments, investing, or sensitive-data domain. - Familiarity with authentication, identity, permissions, privacy, and secure data flows. - Experience building dashboards, data visualizations, or insight-oriented products. - Familiarity with observability, experimentation, product metrics, and iterative development. - Experience with applied AI, conversational interfaces, or systems that incorporate model-generated output. 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

Experience building backend services using Python, Go, Node.js, or comparable technologies.\nExperience with frontend development using React / TypeScript, or Swift or Kotlin.\nExperience operating consumer products or distributed systems at scale.\nExperience with fintech, personal finance, banking, payments, investing, or sensitive-data domain.\nFamiliarity with authentication, identity, permissions, privacy, and secure data flows.\nExperience building dashboards, data visualizations, or insight-oriented products.\nFamiliarity with observability, experimentation, product metrics, and iterative development.\nExperience with applied AI, conversational interfaces, or systems that incorporate model-generated output.

- Own full-stack product features from user experience and frontend implementation through backend services, data models, deployment, and observability.\n- Build polished, accessible, and performant interfaces for account connection, dashboards, insights, and conversational workflows.\n- Design APIs and backend systems that safely ingest, normalize, and serve financial data.\n- Build resilient integrations that handle synchronization, data freshness, partial failures, permissions, and user consent.\n- Bring new AI capabilities into production while prioritizing grounding, accuracy, transparency, and user control.\n- Establish architecture, performance standards, testing practices, and operational safeguards for a fast-growing product area.\n- Debug and improve complex behavior across client, server, infrastructure, and external integrations.\n- Use qualitative feedback, product metrics, and experiments to improve user outcomes without compromising clarity or trust.\n- Collaborate across disciplines to turn ambiguous product opportunities into simple, reliable experiences.