Forward deployed engineering at OpenAI
We partner with organizations to solve high-impact problems using AI—starting from first principles and deploying systems in real-world environments.
Forward deployed engineering (FDE) is how OpenAI brings AI into production for complex, real-world use cases.
Instead of starting with a general product, FDE teams work directly with customers to solve a specific problem, validate impact, and then identify patterns that can scale.
This approach helps organizations move from AI experimentation to reliable deployment.
FDE teams operate in high-ambiguity environments where traditional software approaches break down.
Build from first principles
Prioritize speed and real-world impact
Work directly with domain experts
Deliver early value, then iterate toward scale
The goal is simple: make AI systems that work in practice, not just in theory.
BBVA partnered with OpenAI to help build an AI native bank at global scale. What began as an early deployment of ChatGPT Enterprise quickly expanded across the organization, helping employees improve workflows, enhance decision making, and deliver better customer experiences. Today, the collaboration is scaling to 120,000 employees across 25 countries with AI embedded into the core of how the bank operates.
We partnered with John Deere to deploy AI-powered recommendations for farmers during planting season. After reviewing hundreds of real-world examples with domain experts, building custom evaluation systems to measure accuracy, and iterating quickly to improve model performance, John Deere was able to help farmers reduce chemical usage by 70% and 6x their customer engagement.
By solving real customer problems, our forward deployed engineering teams identify repeatable patterns that evolve into product capabilities. This cycle—build, prove, generalize—connects deployment to product development across Agent SDK, AI-assisted authoring systems, model benchmarking and reliability tools, and more.