Backend Software Engineer - Codex for Finance

ABOUT THE TEAM

OpenAI for Financial Services is part of OpenAI's Verticals organization, which focuses on accelerating the economy and knowledge work. We build AI products for financial institutions and the professionals who power them, from investment bankers and research analysts to investors and other financial services teams.

We combine OpenAI's models, financial data, and enterprise knowledge to help professionals research companies, analyze markets, and produce high-quality work in the tools they use every day.

We're a small, entrepreneurial team working closely with customers and partners across research, product, design, engineering, and go-to-market to bring new capabilities from idea to production.

ABOUT THE ROLE

We're looking for backend engineers to build the systems that make advanced AI useful, reliable, and trustworthy in financial services. You'll build the data systems, agentic workflows, and enterprise integrations behind our products. You'll also help bring them into production at some of the world's largest financial institutions.

This is a product-minded engineering role with significant ownership and zero-to-one building. You'll shape new products from the ground up, work directly with customers to understand their workflows, and collaborate across OpenAI to turn new model capabilities into products that professionals can trust with high-stakes work.

IN THIS ROLE, YOU WILL

• Design and build backend systems that power AI-native financial workflows across ChatGPT Work and Codex.

• Build infrastructure to ingest, index, retrieve, and serve financial data, company filings, market information, and firm-specific knowledge at scale.

• Develop integrations with financial data providers, enterprise knowledge systems, and customer environments, including the authentication, authorization, and entitlements required to use them securely.

• Build the systems that let models and agents use the right tools and data, preserve source provenance, and produce accurate, verifiable outputs.

• Improve the reliability, latency, observability, and quality of production systems, and develop evaluations that measure how well they perform on real financial workflows.

• Work directly with financial institutions to understand customer needs, unblock deployments, and turn feedback into meaningful product improvements.

• Partner with product, design, research, security, and other engineering teams to take new capabilities from early prototype to scaled production.

YOU MIGHT THRIVE IN THIS ROLE IF YOU HAVE

• 5+ years of professional software engineering experience, with a strong track record of building and operating production backend systems.

• Proficiency in one or more backend languages, such as Python, Go, Rust, or TypeScript, and a strong foundation in APIs, data systems, and distributed systems.

• Experience building data-intensive applications, search or retrieval systems, infrastructure platforms, or complex integrations.

• Strong product instincts and the ability to move from an ambiguous customer problem to a practical, well-engineered solution.

• Comfort working across the stack and organizational boundaries when that is what it takes to ship a great product.

• A high bar for reliability, security, privacy, and performance, particularly in enterprise or other high-trust environments.

• Interest in AI and how model capabilities can be applied to complex professional work; direct AI/ML or financial services experience is helpful but not required.

• Experience as a founder, an early engineer at a startup, or an engineer who has helped build a new product from scratch is a plus.

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 t

Responsibilities

• Design and build backend systems that power AI-native financial workflows across ChatGPT Work and Codex.
• Build infrastructure to ingest, index, retrieve, and serve financial data, company filings, market information, and firm-specific knowledge at scale.
• Develop integrations with financial data providers, enterprise knowledge systems, and customer environments, including the authentication, authorization, and entitlements required to use them securely.
• Build the systems that let models and agents use the right tools and data, preserve source provenance, and produce accurate, verifiable outputs.
• Improve the reliability, latency, observability, and quality of production systems, and develop evaluations that measure how well they perform on real financial workflows.
• Work directly with financial institutions to understand customer needs, unblock deployments, and turn feedback into meaningful product improvements.
• Partner with product, design, research, security, and other engineering teams to take new capabilities from early prototype to scaled production.

Requirements

• 5+ years of professional software engineering experience, with a strong track record of building and operating production backend systems.
• Proficiency in one or more backend languages, such as Python, Go, Rust, or TypeScript, and a strong foundation in APIs, data systems, and distributed systems.
• Experience building data-intensive applications, search or retrieval systems, infrastructure platforms, or complex integrations.
• Strong product instincts and the ability to move from an ambiguous customer problem to a practical, well-engineered solution.
• Comfort working across the stack and organizational boundaries when that is what it takes to ship a great product.
• A high bar for reliability, security, privacy, and performance, particularly in enterprise or other high-trust environments.

Preferred Qualifications

• Interest in AI and how model capabilities can be applied to complex professional work; direct AI/ML or financial services experience is helpful but not required.
• Experience as a founder, an early engineer at a startup, or an engineer who has helped build a new product from scratch is a plus.