Engineering Manager, ChatGPT Search Infrastructure
San Francisco • FullTime
Posted 4d ago
Remote Work Policy
On-site
Employment Type
FullTime
Categories
AI Infrastructure Engineer
About the job
We are seeking an Engineering Manager to lead the ChatGPT Search Infrastructure team. This role involves setting the technical and organizational direction for systems that integrate search capabilities into ChatGPT, guiding architectural decisions across various components like search orchestration, model integration, serving infrastructure, and observability. A key responsibility is creating leverage for Search product verticals by developing extensible platforms that enable independent feature development, testing, and launching with strong guardrails for reliability, scalability, and quality. The ideal candidate will possess technical depth across the full search stack, understand and influence partner systems, and lead complex workstreams to translate emerging model and search capabilities into reliable, global-scale experiences.
Responsibilities
- Define and drive the technical strategy, architecture, and roadmap for ChatGPT Search Infrastructure.
- Lead and develop a team of experienced engineers, fostering an inclusive culture.
- Partner with Post-Training on model launches, experiments, and prompt optimization.
- Build reusable platforms for Search product vertical teams to independently implement and launch features.
- Partner with Inference, Indexing, and Retrieval teams to evolve the end-to-end Search architecture.
- Define and uphold service objectives for availability, latency, and scalability.
- Establish strong engineering practices across system design, testability, observability, and operational readiness.
- Lead complex workstreams, remove bottlenecks, and build alignment across teams in ambiguous environments.
Requirements
- Experience managing senior engineers and leading teams responsible for complex, high-scale infrastructure or distributed systems.
- Significant technical depth in backend infrastructure, platform engineering, APIs, low-latency serving, or AI-powered product development.
- Understanding of how models, prompts, inference systems, search orchestration, indexing, retrieval, and infrastructure work together.
- Experience partnering with research or Post-Training teams to launch models and optimize prompts in production.
- Experience building shared platforms for other engineering teams.
- Experience shaping the architecture of systems with demanding availability, latency, and scale requirements.
- Ability to balance technical depth, product strategy, and organizational leadership.
- Ability to build strong cross-functional partnerships and empower engineers.