OpenAI

Software Engineer, GPU Infrastructure- ChatGPT Engineering

OpenAI3 days ago
Location

London, UK

Type

Full Time

Salary

USD 180,000 – 300,000

Level

Senior

Role

Infrastructure Engineer

Posted

Jul 9, 2026

Full TimeSenior

The role

Summary

Join OpenAI's ChatGPT Engineering team to design and operate GPU infrastructure powering one of the world's largest AI products. This role offers the opportunity to build scalable systems managing thousands of GPUs, develop intelligent automation tooling, and directly impact AGI development through infrastructure improvements. You'll work across production engineering, distributed systems, and capacity management with 5+ years of production infrastructure experience and expertise in systems languages, Kubernetes, and distributed systems design.

What you'll do

Design and operate GPU infrastructure management systems: Design, build, and operate software systems that manage large-scale GPU clusters supporting ChatGPT inference workloads. This includes developing core infrastructure services for fleet orchestration, resource allocation, and compute platform operations supporting millions of concurrent inference requests.
Build internal platforms and AI-powered automation: Develop internal platforms, tooling, and intelligent agents that automate fleet operations, reduce manual intervention, and enable self-healing infrastructure. Create systems that leverage AI to predict and prevent infrastructure issues before they impact production workloads.
Improve observability, reliability, and efficiency: Enhance observability and monitoring across thousands of GPUs to achieve high reliability and operational efficiency. Implement comprehensive distributed tracing, metrics collection, and alerting systems that provide real-time insights into fleet health and performance.
Develop capacity planning and fleet health systems: Build and maintain systems for capacity planning, intelligent scheduling, fleet health monitoring, and automated incident response. Create data-driven tools that optimize GPU utilization while ensuring service level agreements are consistently met.
Identify and eliminate infrastructure bottlenecks: Analyze production infrastructure to identify performance bottlenecks and scalability constraints. Implement solutions that improve resource utilization, reduce operational latency, and enable the infrastructure to scale with demand.
Cross-team collaboration and platform improvement: Partner closely with research, platform, networking, and systems teams to continuously improve the compute platform. Establish engineering best practices around operational excellence, infrastructure automation, and reliability patterns.

What we look for

Technical

Systems programming languagesStrong programming proficiency in Go, Python, C++, Rust, or similar systems-level languages for building high-performance infrastructure software.
Distributed systems architectureDeep understanding of distributed systems concepts including consensus protocols, eventual consistency, fault tolerance, and designing systems for high availability and scalability.
Linux systems expertiseComprehensive knowledge of Linux kernel internals, system performance tuning, networking concepts, and low-level system debugging techniques.
Observability toolingExperience with observability and monitoring stacks including metrics collection, distributed tracing, log aggregation, and alerting systems.
Systems design and debuggingExcellent systems design skills with strong debugging capabilities for complex production issues, performance analysis, and infrastructure troubleshooting.
High-performance computing knowledgeUnderstanding of GPU architecture, compute optimization, performance profiling, and resource management for compute-intensive workloads.

Education

Computer Science or related fieldBachelor's degree in Computer Science, Engineering, or related field, or equivalent professional experience demonstrating systems-level expertise.

Experience

Production infrastructure operations5+ years of software engineering experience building and operating production infrastructure systems, with proven track record managing large-scale distributed systems in production environments.
GPU or compute infrastructureDemonstrated experience operating GPU infrastructure, high-performance computing clusters, ML infrastructure platforms, or other large-scale compute platforms at production scale.
Kubernetes and container orchestrationHands-on experience with Kubernetes, cloud infrastructure platforms, Linux systems administration, and container orchestration technologies in production environments.
Distributed systems design and operationsExperience designing and operating highly available distributed systems with focus on reliability, fault tolerance, and high availability patterns in production settings.
Observability and monitoringStrong background in infrastructure observability, monitoring systems, capacity planning, incident management, and root cause analysis of production issues.
Infrastructure automationProven ability to build software that automates operational workflows and reduces manual operational overhead through infrastructure automation and tooling.

Skills

Required skills

Go programmingProduction experience with Go for building scalable infrastructure services and tooling
PythonProficiency in Python for infrastructure automation, scripting, and systems tools
KubernetesHands-on experience deploying, scaling, and debugging Kubernetes clusters in production
Linux administrationDeep knowledge of Linux system administration, kernel concepts, and system performance tuning
Distributed systemsStrong understanding of distributed systems design patterns, consensus algorithms, and fault tolerance
Cloud infrastructureExperience with cloud platforms and infrastructure-as-code principles
Monitoring and observabilityExperience building or operating monitoring systems, metrics collection, and alerting infrastructure
Production debuggingProven ability to diagnose and resolve complex production infrastructure issues

Nice to have

C++ or RustExperience with C++ or Rust for high-performance systems programming
GPU infrastructure experiencePrevious experience managing GPU clusters or working with NVIDIA GPU infrastructure
ML infrastructure platformsFamiliarity with ML training infrastructure or large-scale ML platform operations
Network programmingKnowledge of network protocols, socket programming, and network optimization
Production engineering backgroundBackground in SRE, Production Engineering, or Platform Engineering roles
AI-powered systemsExperience building systems that leverage AI for operational automation or prediction
Capacity planning toolsExperience developing capacity planning or resource optimization systems

Compensation & benefits

Salary

USD 180,000 – 300,000 (annual)

Stock options

Available

Benefits

Competitive equity package

Significant stock options as part of compensation package, providing upside participation in OpenAI's growth

Comprehensive health and wellness

Medical, dental, and vision insurance coverage with focus on employee wellbeing

Retirement planning

401(k) plan with company matching to support long-term financial security

Flexible work arrangements

Collaborative work environment designed for distributed and flexible working patterns

Professional development

Opportunity to work at the frontier of AI infrastructure with exposure to cutting-edge technology and industry-leading engineering practices

Impact-driven mission

Opportunity to directly influence AGI development through infrastructure improvements benefiting millions of users globally

Inclusive workplace

Commitment to diverse perspectives and inclusive culture where all backgrounds can do their best work

Learning and growth

Access to world-class engineering talent and exposure to large-scale infrastructure challenges solving real-world problems

Interview process

  1. 1
    Initial screening call — Recruiter conversation to discuss your background, experience with infrastructure systems, and alignment with the role's technical requirements
  2. 2
    Technical assessment — In-depth technical discussion covering systems design, infrastructure architecture, production debugging, and problem-solving approaches
  3. 3
    Infrastructure systems design interview — Whiteboard-style systems design interview focused on designing large-scale GPU infrastructure systems, capacity planning, and operational automation
  4. 4
    Operational problem-solving — Interview discussing real infrastructure challenges, incident response approaches, and how you'd approach operational problem-solving at scale
  5. 5
    Cross-team collaboration discussion — Conversation with team members about collaboration style, communication skills, and experience working across research, platform, and product teams
  6. 6
    Leadership conversation — Meeting with engineering leadership to discuss vision for infrastructure, long-term goals, and philosophy on infrastructure reliability and automation
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OpenAI

OpenAI

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OpenAI is an American artificial intelligence research organization developing advanced AI models like GPT. Focused on ensuring AI benefits humanity, it creates tools for natural language processing and generative AI applications.

San Francisco, California, United StatesFounded 2015openai.com

Tech Stack

Languages
GoPythonC++Rust
Frameworks
KubernetesDocker
Databases
Time-series databasesDistributed databases
Tools
PrometheusGrafanaGitLinuxCloud platforms
Other
Infrastructure-as-CodeGPU architecture and optimizationDistributed tracingIncident management

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