# Engineering Manager, ChatGPT Search Infrastructure
**Company:** [OpenAI](https://scaleengineer.com/companies/openai)
Lead the ChatGPT Search Infrastructure team at OpenAI, responsible for building foundational systems that power search experiences across ChatGPT. This Engineering Manager role requires deep technical expertise in distributed systems, large-scale infrastructure, and AI product development, combined with strong people leadership to manage senior engineers and drive cross-functional collaboration across post-training, product, inference, and infrastructure teams.
**Role:** Engineering Manager
**Seniority:** Manager
**Locations:** San Francisco
**Salary:** 401000–445000 USD
[Apply](https://jobs.ashbyhq.com/openai/9d6520c0-4c28-472f-ae1f-82b03ee9429d)
Canonical: https://scaleengineer.com/jobs/openai/engineering-manager-chatgpt-search-infrastructure
---
## Responsibilities

- Define Technical Strategy and Architecture: Establish and drive the technical strategy, architecture, and roadmap for ChatGPT Search Infrastructure spanning search orchestration, APIs, model and prompt integration, serving infrastructure, experimentation frameworks, evaluation systems, observability platforms, and product integrations. Lead architectural decisions that balance immediate product requirements with long-term reliability, scalability, latency optimization, and platform maintainability at global scale.
- Lead and Develop Engineering Team: Build and mentor a high-performing team of experienced engineers, creating meaningful ownership opportunities for major technical areas and complex workstreams. Foster an inclusive, high-trust culture characterized by clear accountability, elevated performance standards, and professional growth, while removing technical and organizational bottlenecks that impede team velocity.
- Build Extensible Platform Infrastructure: Design and develop reusable, extensible platforms that enable independent Search product vertical teams to implement, test, and launch features without ongoing infrastructure team involvement. Implement automated guardrails, comprehensive testing capabilities, and observability features that protect reliability, scalability, latency, and quality while enabling rapid feature iteration and deployment.
- Partner with Post-Training and Research Teams: Collaborate closely with Post-Training teams on model launches, A/B experimentation frameworks, search behavior evaluation, and prompt optimization. Translate model improvements and research innovations into production-ready product experiences, ensuring seamless integration between emerging model capabilities and search infrastructure serving systems.
- Evolve End-to-End Search Architecture: Partner with Inference, Indexing, and Retrieval teams to continuously evolve the complete search stack architecture, adapt serving optimizations, improve model-infrastructure co-design, and enhance product outcomes across distributed systems. Drive alignment on performance objectives, scalability requirements, and infrastructure efficiency across multiple organizational teams.
- Define and Uphold Service Objectives: Establish and maintain demanding service level objectives including 99.9% minimum availability targets, sub-second latency requirements aligned with user experience demands, and elasticity to support ChatGPT's sustained growth trajectory. Design systems with built-in testability, observability, safe rollout capabilities, and operational readiness to prevent incidents and enable rapid incident response.
- Establish Engineering Excellence Practices: Implement and enforce strong engineering practices across system design, automated testing, production observability, experimentation infrastructure, capacity planning, safe rollout procedures, operational readiness, and incident prevention. Build a culture of technical excellence where reliability, scalability, and maintainability are prioritized alongside feature velocity.
- Lead Cross-Functional Collaboration: Independently manage multiple complex technical workstreams while building strong cross-functional partnerships with product, research, Post-Training, Search Quality, Inference, Indexing, Retrieval, and infrastructure teams. Exercise strong judgment in ambiguous environments, translate emerging capabilities into reliable experiences, and align diverse teams around shared technical vision and roadmap objectives.

## Requirements

### education

- {"name":"Bachelor's Degree in Computer Science or Related Field","description":"Formal education in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Physics, or equivalent field providing foundational knowledge in algorithms, systems design, and software engineering principles. Advanced degree (Master's or PhD) in relevant field is a plus but not required with sufficient industry experience."}

### technical

- {"name":"Backend Infrastructure and Distributed Systems","description":"Demonstrated expertise designing and operating complex, large-scale distributed systems with demanding availability, latency, and throughput requirements. Deep understanding of system design principles, performance optimization, horizontal scaling patterns, fault tolerance, consistency models, and operational reliability at production scale."}
- {"name":"Platform Engineering and Abstraction Design","description":"Proven experience building shared platform infrastructure, developer APIs, and abstractions that enable teams to independently develop and launch features within guardrailed parameters. Expertise in designing extensible systems with strong interfaces, automated safety mechanisms, comprehensive testing frameworks, and observability that prevent regressions."}
- {"name":"Low-Latency Serving and Online Systems","description":"Strong background in designing and optimizing low-latency serving infrastructure, real-time data systems, and online prediction serving for latency-sensitive workloads. Experience with serving optimization, request routing, caching strategies, and performance profiling to achieve sub-second response times at scale."}
- {"name":"Experimentation Platforms and A/B Testing","description":"Comprehensive knowledge of building experimentation infrastructure, A/B testing frameworks, statistical analysis systems, and feature flagging platforms. Experience designing systems that enable rapid, safe experimentation with proper statistical rigor, rollout controls, and observability for validating product hypotheses."}
- {"name":"Search Systems and Information Retrieval","description":"Deep understanding of how search systems, indexing, retrieval algorithms, ranking, and relevance evaluation work at scale. Knowledge of search infrastructure components, query optimization, result ranking, and integration with AI models to deliver accurate, relevant search results within latency constraints."}
- {"name":"AI Model Serving and Integration","description":"Strong expertise in integrating large language models into production systems, model serving infrastructure, prompt engineering, model behavior evaluation, and inference optimization. Understanding of how models, inference systems, and search orchestration combine to create end-to-end user experiences."}

### experience

- {"name":"Senior Engineering Leadership Experience","description":"Minimum 5-8 years of progressive leadership experience managing senior engineers, with demonstrated success building high-performing teams responsible for complex infrastructure systems. Track record of recruiting, mentoring, and developing strong engineering talent, and creating cultures of technical excellence and accountability."}
- {"name":"Large-Scale Infrastructure Leadership","description":"Significant experience leading platform, infrastructure, or backend teams responsible for systems serving millions of requests, supporting millions of users, or operating at global scale. Proven ability to balance shipping product features with maintaining reliability, performance, and scalability as scale increases exponentially."}
- {"name":"Cross-Functional Product Development","description":"Experience partnering with research, product, post-training, or machine learning teams to launch AI models, run controlled experiments, evaluate model behavior in production, and translate research innovations into product experiences. Understanding of how to collaborate across organizational boundaries in ambiguous, rapidly-evolving environments."}
- {"name":"End-to-End System Architecture","description":"Proven experience shaping architecture of demanding systems with high availability, low-latency, and scale requirements, with testability, observability, and operational excellence designed in from inception. Track record of making sound architectural tradeoffs, designing for resilience, and evolving systems as requirements scale."}
- {"name":"Platform Abstraction Design","description":"Demonstrated success building reusable platform abstractions, shared infrastructure layers, and developer-friendly APIs that enable other teams to operate independently while maintaining reliability and performance guardrails. Evidence of balancing platform generality with specific product needs."}

## Skills

### required

- {"name":"Distributed Systems Architecture","description":"Deep expertise designing systems with high availability, consistency requirements, fault tolerance, and scalability. Proficiency with distributed consensus, replication strategies, load balancing, and handling failure scenarios in production environments."}
- {"name":"Backend Engineering Leadership","description":"Strong ability to lead technical strategy for complex backend systems, make architectural decisions with incomplete information, and translate vision into executable roadmaps. Expertise in setting technical direction that balances innovation with operational stability."}
- {"name":"Team Building and Mentorship","description":"Proven capability building high-performing engineering teams, developing individual engineers, delegating ownership, and creating sustainable team cultures. Strong emotional intelligence, communication skills, and ability to attract and retain top talent."}
- {"name":"Cross-Functional Collaboration","description":"Demonstrated excellence partnering across product, research, infrastructure, and other technical teams to align on shared objectives. Ability to negotiate technical tradeoffs, build consensus in ambiguous situations, and translate between different technical and business perspectives."}
- {"name":"Observability and Monitoring","description":"Expertise designing comprehensive observability systems, metrics collection, logging infrastructure, and alerting frameworks. Understanding of SLI/SLO definitions, error budgets, and using data to drive operational decisions and reliability improvements."}
- {"name":"Performance Optimization","description":"Strong skills in identifying performance bottlenecks, profiling systems, optimizing critical paths, and achieving latency targets. Experience with caching strategies, indexing, query optimization, and infrastructure tuning for low-latency serving."}
- {"name":"Production Operations","description":"Solid understanding of deployment pipelines, incident response, change management, capacity planning, and operational runbooks. Experience designing systems for operational resilience with built-in safety mechanisms, rollback capabilities, and reliable deployment procedures."}
- {"name":"Strategic Roadmap Planning","description":"Ability to develop multi-quarter technical roadmaps that align infrastructure evolution with product requirements, capacity planning, and technical debt management. Skill in communicating roadmap rationale to stakeholders and driving execution against complex dependencies."}

### preferred

- {"name":"Large Language Model Integration","description":"Experience integrating LLMs or large AI models into production systems, optimizing for inference latency, and understanding model behavior and reliability considerations. Knowledge of prompt engineering, model evaluation in production, and model-infrastructure co-design."}
- {"name":"Search Infrastructure Experience","description":"Background building or operating search systems at scale, including indexing, ranking, retrieval optimization, and relevance evaluation. Understanding of how search integrates with ranking algorithms, personalization, and serving infrastructure."}
- {"name":"ML Systems and MLOps","description":"Familiarity with machine learning systems architecture, model serving platforms, experiment tracking, and the operational challenges of running ML in production. Understanding of model validation, monitoring, retraining pipelines, and ML-specific observability."}
- {"name":"GPU Infrastructure and Optimization","description":"Experience with GPU cluster management, CUDA optimization, inference acceleration, or distributed GPU training. Understanding of GPU-specific performance considerations and infrastructure efficiency for compute-intensive workloads."}
- {"name":"API Design and Microservices","description":"Strong experience designing clean, scalable APIs for platform infrastructure, microservices architecture patterns, service discovery, and inter-service communication. Understanding of API versioning, backward compatibility, and evolving APIs without disrupting consumers."}
- {"name":"A/B Testing Platforms","description":"Direct experience building or operating A/B testing frameworks, experiment randomization, statistical analysis systems, and feature flagging infrastructure. Understanding of statistical validity, sample size calculations, and controlling for multiple hypothesis testing."}

## Tech stack

### tools

### others

### databases

### languages

### frameworks

## Benefits

### benefits

## Compensation

- **max:** 500000
- **min:** 350000
- **currency:** USD
- **stockOptions:** true

## Interview process

### steps

## Full description
**About the Team**

The ChatGPT Search Infrastructure team builds the foundational systems that power search experiences across ChatGPT. We develop the infrastructure that connects models with search systems and other sources of real-time information, enabling ChatGPT to deliver timely, relevant, and trustworthy answers to users around the world.

Our work sits at the intersection of product engineering, AI, and large-scale infrastructure. We build shared platforms and abstractions that enable product teams to independently develop, evaluate, and launch new search-powered experiences. These platforms provide the guardrails, testing capabilities, observability, and rollout controls needed to prevent reliability, scalability, quality, and latency regressions while supporting rapid product iteration.

The team partners closely with:

* Post-Training on model launches, experimentation, and prompt optimization
* Search product verticals on new user experiences
* Inference on GPU efficiencies
* Indexing and Retrieval on the systems that identify and deliver relevant information
* Capacity/Fleet team to ensure optimal regionalized provisioning of GPUs and CPUs

**About the Role**

We are looking for an Engineering Manager to lead the team responsible for ChatGPT’s Search Infrastructure.

You will set the technical and organizational direction for the systems that bring search capabilities into ChatGPT. You will guide architectural decisions across search orchestration, model and prompt integration, serving infrastructure, experimentation, observability, evaluation, and product integrations. You will balance immediate launch and product needs with the long-term reliability, scalability, latency, and maintainability of the platform.

A central responsibility of this role is creating leverage for Search product verticals. You will lead the development of extensible platforms that allow those teams to independently build, test, and launch features without requiring ongoing involvement from the core infrastructure team. These platforms must include strong interfaces and automated guardrails that enable fast iteration while protecting the reliability, scalability, latency, and quality of ChatGPT Search.

This role requires technical depth across the full Search stack and the ability to understand and influence systems owned by partner teams. You will be expected to develop a coherent technical direction across model behavior, inference, search orchestration, indexing, retrieval, experimentation, and infrastructure—even when execution spans multiple organizational boundaries.

You will lead multiple complex workstreams, empower experienced engineers to own major technical areas, and partner with product, research, Post-Training, Search Quality, Inference, Indexing, Retrieval, and infrastructure teams to translate emerging model and search capabilities into reliable experiences operating at global scale.

**In this role, you will:**

* Define and drive the technical strategy, architecture, and roadmap for ChatGPT Search Infrastructure, spanning search orchestration, APIs, model and prompt integration, serving, experimentation, evaluation, observability, and product integrations.
* Lead and develop a team of experienced engineers, create meaningful ownership opportunities, and foster an inclusive, high-trust culture with clear accountability and high standards.
* Partner with Post-Training on model launches, A/B experiments, search-behavior evaluation, and prompt optimization, translating model improvements into production-ready product experiences.
* Build reusable platforms that enable Search product vertical teams to independently implement, test, and launch features, with automated guardrails that protect reliability, scalability, quality, and latency.
* Partner with Inference, Indexing, and Retrieval teams to evolve the end-to-end Search architecture, adapt serving optimizations, and improve product outcomes across the stack.
* Define and uphold service objectives of at least 99.9% availability, sub-second latency where required by the user experience, and the scalability needed to support ChatGPT’s continued growth.
* Establish strong engineering practices across system design, testability, observability, experimentation, capacity planning, rollout safety, operational readiness, and incident prevention.
* Independently lead multiple complex workstreams, remove technical and organizational bottlenecks, and build alignment across product, research, and infrastructure teams in ambiguous and rapidly changing environments.

**You might thrive in this role if you:**

* Have experience managing senior engineers and leading teams responsible for complex, high-scale infrastructure, online serving, or distributed systems.
* Bring significant technical depth in backend infrastructure, platform engineering, APIs, low-latency serving, experimentation platforms, or AI-powered product development.
* Understand how models, prompts, inference systems, search orchestration, indexing, retrieval, and infrastructure work together to deliver an end-to-end user experience.
* Have partnered with research or Post-Training teams to launch models, run controlled experiments, evaluate model behavior, or optimize prompts in production.
* Have built shared platforms that allow other engineering teams to independently develop and launch features within well-defined reliability, scalability, quality, and performance guardrails.
* Have shaped the architecture of systems with demanding availability, latency, and scale requirements, with testability, observability, safe rollout, and operational excellence built in from the outset.
* Can move comfortably between technical depth, product strategy, organizational leadership, and people management while exercising strong judgment in ambiguous environments.
* Build strong cross-functional partnerships, empower experienced engineers to lead, and care deeply about developing people and creating an inclusive, sustainable team culture.

**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. 

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