Software Engineer, Search Infrastructure

About the Team

The Search Product Infrastructure team builds the systems that power search experiences across ChatGPT. We partner with teams developing models, operating inference infrastructure, building specialized search experiences, and maintaining search indexes to bring advances in models and retrieval into production. Our work spans search orchestration, model serving, experimentation, and distributed systems, with direct impact on answer quality, responsiveness, reliability, and efficiency at ChatGPT scale.

About the Role

As a senior engineer on the Search Product Infrastructure team, you will design, build, and operate the systems that connect models with search at ChatGPT scale. You will tackle challenges in search orchestration, inference efficiency, experimentation, and production reliability, making tradeoffs that directly shape answer quality and user experience. Working closely with researchers and partner engineering teams, you will own projects from technical design through launch and iteration, evolving the architecture as models, product capabilities, and demand grow.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will

• Design and evolve the services that coordinate search classification, retrieval, ranking, and model inference, working closely with researchers and partner engineering teams to bring new capabilities into production.

• Improve end-to-end latency, throughput, and infrastructure efficiency through profiling, caching, request routing, and capacity planning, making informed tradeoffs between search quality, reliability, and compute cost.

• Build experimentation tooling and automation to run reproducible A/B tests, define success metrics, and measure product impact. Use shadow traffic and load testing to validate system behavior, estimate capacity needs, and support safe production rollouts.

• Own production reliability through observability, resilient fallback behavior, incident response, and automation that improves launch safety and reduces operational toil.

• Build search APIs and tool interfaces that enable models and agents to retrieve information reliably while respecting access controls and preserving source attribution.

You might thrive in this role if you

• Have significant experience designing, building, and operating large-scale distributed systems, with depth in performance, reliability, or resource efficiency.

• Bring experience in one or more of search, information retrieval, ML infrastructure, inference serving, or other high-throughput online systems.

• Have strong programming and systems debugging skills, and are comfortable working across languages and unfamiliar parts of a production stack.

• Can turn ambiguous product or research needs into clear technical plans, align partners across teams, and carry projects through deployment and measurable results.

• Enjoy learning across systems and ML, investigating unfamiliar problems, and sharing technical decisions and lessons clearly with others.

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 an

Responsibilities

• Design and evolve the services that coordinate search classification, retrieval, ranking, and model inference, working closely with researchers and partner engineering teams to bring new capabilities into production.
• Improve end-to-end latency, throughput, and infrastructure efficiency through profiling, caching, request routing, and capacity planning, making informed tradeoffs between search quality, reliability, and compute cost.
• Build experimentation tooling and automation to run reproducible A/B tests, define success metrics, and measure product impact. Use shadow traffic and load testing to validate system behavior, estimate capacity needs, and support safe production rollouts.
• Own production reliability through observability, resilient fallback behavior, incident response, and automation that improves launch safety and reduces operational toil.
• Build search APIs and tool interfaces that enable models and agents to retrieve information reliably while respecting access controls and preserving source attribution.

Requirements

• Significant experience designing, building, and operating large-scale distributed systems, with depth in performance, reliability, or resource efficiency.
• Experience in one or more of search, information retrieval, ML infrastructure, inference serving, or other high-throughput online systems.
• Strong programming and systems debugging skills, and are comfortable working across languages and unfamiliar parts of a production stack.
• Can turn ambiguous product or research needs into clear technical plans, align partners across teams, and carry projects through deployment and measurable results.
• Enjoy learning across systems and ML, investigating unfamiliar problems, and sharing technical decisions and lessons clearly with others.

• Relocation assistance to new employees