Software Engineer, Search Infrastructure

Senior Backend Engineer · Senior · Full Time

San FranciscoUSD 266k – 445k4w ago
Apply for this role

Opens OpenAI's application page

Role

What you'll do.

Join OpenAI's Search Product Infrastructure team to design and operate large-scale distributed systems powering search experiences across ChatGPT. As a Senior Software Engineer, you'll architect search orchestration, inference serving, and experimentation platforms that directly impact answer quality and user experience at scale, working across search retrieval, ML infrastructure, and production reliability across a hybrid San Francisco-based role.

Responsibilities

  • Design and Evolve Search Infrastructure Services: Architect and maintain services that coordinate search classification, retrieval, ranking, and model inference at ChatGPT scale. Work closely with ML researchers and partner engineering teams to translate research breakthroughs into production-grade infrastructure, ensuring seamless integration of new search capabilities into the live platform while maintaining system stability and performance.
  • Optimize End-to-End Performance and Efficiency: Drive continuous improvement of latency, throughput, and resource utilization across the search infrastructure stack. Conduct systematic performance profiling and optimization initiatives including intelligent caching strategies, request routing optimization, and capacity planning. Balance engineering tradeoffs between search quality, system reliability, and compute costs to deliver optimal user experience while managing infrastructure expenses.
  • Build and Maintain Experimentation Frameworks: Design and develop experimentation tooling and automation systems that enable reproducible A/B testing at scale. Define and track success metrics, measure quantifiable product impact, and leverage shadow traffic and load testing techniques to validate system behavior. Establish rigorous protocols for capacity estimation and safe production rollouts, enabling data-driven decision making across the organization.
  • Own Production Reliability and Operational Excellence: Establish and maintain production reliability standards through comprehensive observability, resilient fallback mechanisms, and systematic incident response protocols. Build automation to improve launch safety, reduce operational toil, and enable on-call engineers to respond effectively to production issues. Implement monitoring, alerting, and runbook documentation that supports 24/7 system reliability.
  • Develop Search APIs and Tool Interfaces: Build robust search APIs and tool interfaces that enable AI models and agents to retrieve information reliably in production environments. Implement access control mechanisms and maintain source attribution across retrieved results. Design interfaces that support both current needs and future agent capabilities while ensuring data integrity and user privacy.

Qualifications

What we look for.

Technical

  • Distributed Systems Design

    Deep expertise designing, building, and operating large-scale distributed systems in production environments. Must demonstrate understanding of system design patterns, load balancing, service orchestration, fault tolerance, and scaling strategies. Experience with systems handling millions of concurrent requests or petabytes of data preferred.

  • Performance and Reliability Engineering

    Proven track record optimizing system performance for latency, throughput, and resource efficiency. Hands-on experience with profiling tools, performance metrics, benchmarking methodologies, and production debugging. Strong understanding of reliability engineering principles, SLOs, observability, and incident response procedures.

  • Search and Information Retrieval Systems

    Experience building or operating search infrastructure, information retrieval systems, or ranking engines. Knowledge of search algorithms, indexing strategies, query processing, and retrieval optimization. Experience with search frameworks or technologies such as Elasticsearch, Solr, or similar platforms is valuable.

  • ML Infrastructure and Inference Serving

    Experience working with ML model serving platforms, inference optimization, or ML infrastructure. Understanding of model deployment patterns, latency-quality tradeoffs, and serving infrastructure for production AI systems. Familiarity with inference serving frameworks or platforms is beneficial.

  • High-Throughput Online Systems

    Demonstrated experience building and operating high-throughput, low-latency online systems that process real-time requests at scale. Understanding of caching strategies, request routing, and capacity planning for systems serving millions of users or requests per second.

  • Programming and Systems Debugging

    Strong programming fundamentals across multiple languages with ability to rapidly context-switch between unfamiliar codebases. Advanced debugging skills for complex distributed system issues. Comfortable working across the full production stack from frontend to kernel-level optimizations.

Education

  • Computer Science or Equivalent

    Bachelor's degree in Computer Science, related field, or equivalent professional experience. Strong foundation in algorithms, data structures, systems programming, and networking fundamentals is expected.

Experience

  • Large-Scale Systems Engineering

    5+ years of experience designing and operating infrastructure or backend systems at companies with significant scale (billions of requests or millions of concurrent users). Direct involvement in making architectural decisions that impacted system performance, reliability, or cost for production systems.

  • Search or Information Retrieval Engineering

    2+ years of hands-on experience building or operating search, retrieval, ranking, or information discovery systems. Experience could include search engines, recommendation systems, or other retrieval-based platforms in production environments.

  • Inference or ML Infrastructure

    2+ years working on ML infrastructure, model serving, inference optimization, or ML operations. Experience could include optimizing model serving latency, managing inference infrastructure, or building systems that serve ML models in production.

  • Production Reliability and Operations

    Demonstrated track record of owning production systems, implementing reliability improvements, and responding to operational challenges. Experience with observability tools, on-call rotation, incident response, and SLO management.

Skills

Required

  • Python

    Production-level proficiency in Python for systems development, scripting, and infrastructure automation. Used extensively for backend services, tooling, and ML infrastructure at scale.

  • Go

    Experience with Go for building high-performance, concurrent backend systems. Critical for microservices architecture, distributed systems, and infrastructure components at OpenAI's scale.

  • Distributed Systems Architecture

    Deep understanding of distributed systems concepts including consensus algorithms, message queues, eventual consistency, and failure modes. Ability to design systems that scale horizontally and handle partial failures.

  • Database and Caching Systems

    Hands-on experience optimizing queries, designing schemas, and operating both relational and NoSQL databases. Strong knowledge of caching strategies, cache consistency, and storage system tradeoffs.

  • System Observability and Monitoring

    Expertise implementing comprehensive observability including structured logging, metrics collection, and distributed tracing. Ability to design effective alerting strategies and debug production issues using observability tools.

  • API Design and Development

    Proficiency designing and implementing robust APIs that handle scale. Experience with REST principles, gRPC, or other RPC frameworks. Understanding of API versioning, backward compatibility, and documentation.

Preferred

  • Rust

    Nice to have

    Experience with Rust for systems programming, particularly for performance-critical components. Valuable for building efficient infrastructure components and learning modern systems languages.

  • Search Engine Technologies

    Nice to have

    Hands-on experience with Elasticsearch, Solr, Sphinx, or other search engine platforms. Understanding of inverted indexes, query DSLs, and search engine optimization.

  • Information Retrieval

    Nice to have

    Knowledge of ranking algorithms, retrieval techniques, and information retrieval evaluation metrics. Familiarity with concepts like BM25, vector similarity search, or neural ranking models.

  • ML Model Serving

    Nice to have

    Experience with ML serving frameworks like TensorFlow Serving, TorchServe, Triton, or custom serving infrastructure. Understanding of inference optimization and model batching strategies.

  • Cloud Infrastructure

    Nice to have

    Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). Knowledge of infrastructure-as-code and DevOps practices.

  • Experimentation and Metrics

    Nice to have

    Experience designing A/B testing frameworks, defining success metrics, and running controlled experiments at scale. Knowledge of statistical methods for analyzing experimental results.

  • C++

    Nice to have

    Proficiency in C++ for high-performance, low-latency systems. Valuable for optimizing critical path components and understanding systems-level performance considerations.

Tech stack

Languages

PythonGoC++

Frameworks

gRPCProtocol BuffersFastAPI

Databases

PostgreSQLRedisElasticsearch

Tools

KubernetesDockerPrometheusGrafanaDatadog or New RelicGit

Other

Distributed TracingA/B Testing FrameworksLoad Testing ToolsSearch Optimization

Compensation

Pay and benefits.

Base·USD 266,000 – 445,000

Equity·Stock options

Benefits

  • Equity Compensation

    Significant stock options package providing long-term upside participation in OpenAI's growth and success as a leading AI company.

  • Comprehensive Health Coverage

    Full medical, dental, and vision insurance coverage for employees and eligible dependents with OpenAI contributing to premiums.

  • Mental Health and Wellness

    Mental health support, therapy services, and wellness programs to support employee wellbeing and work-life balance.

  • Relocation Assistance

    Full relocation package provided to help new employees relocate to the San Francisco Bay Area, including moving costs and temporary housing support.

  • Flexible Hybrid Work

    Hybrid work arrangement with 3 days per week in San Francisco office and 2 days flexible work location, balancing collaboration with flexibility.

  • 401(k) Retirement Plan

    Employer-sponsored 401(k) retirement savings plan with company matching to support long-term financial planning and retirement security.

  • Professional Development

    Learning and development opportunities, conference attendance budgets, and support for skill development and career growth.

  • Paid Time Off

    Generous paid vacation, sick leave, and personal days to ensure adequate rest and recovery throughout the year.

  • Parental Leave

    Comprehensive parental leave policies supporting employees during critical family milestones and transitions.

  • Commuter Benefits

    Subsidized transit benefits and commuting support to reduce transportation costs for San Francisco Bay Area employees.

Full posting

Original listing.

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 and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

OpenAI Global Applicant Privacy Policy

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

Redirects to OpenAI's application page.

Other roles

More at OpenAI.

View all 127 roles