Software Engineer, Infrastructure Reliability at OpenAI

San Francisco, California, United States

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$255,000 – $405,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, TechnologyIndustries

Requirements

4+ years of relevant industry experience, with 2+ years leading large scale, complex projects or teams as an engineer or tech lead
A passion for distributed systems at scale with a focus on reliability, scalability, security, and continuous improvement
Proven experience as a reliability engineer, production engineer, or a similar role in a fast-paced, rapidly scaling company
Strong proficiency in cloud infrastructure (like AWS, GCP, Azure) and IaC tools such as Terraform
Proficiency in programming / scripting languages
Experience with containerization technologies and container orchestration platforms like Kubernetes
Experience with observability tools such as Datadog, Prometheus, Grafana, Splunk and ELK stack
Experience with microservices architecture and service mesh technologies
Knowledge of security best practices in cloud environments
Strong understanding of distributed systems, networking, and database technologies
Excellent problem-solving skills and ability to work in a fast-paced environment
Deep understanding of distributed systems principles and a proven track record in building and operating scalable and reliable systems
Keen eye for performance and optimization in complex, globally-distributed systems
Experience operating orchestration systems such as Kubernetes at scale and building abstractions over cloud platforms
Comfortable working in Linux environments, and with tools like Kubernetes, Terraform, CI/CD pipelines, and modern observability stacks
Experience collaborating with cross-functional teams to ensure reliability and scalability in design and development
Humble attitude, eagerness to help colleagues, and desire to do whatever it takes to make the team succeed
Own problems end-to-end, willing to pick up missing knowledge
Comfortable with ambiguity and rapid change

Responsibilities

Design, build, and operate reliable and performant systems used across engineering
Identify and fix performance bottlenecks and inefficiencies, ensuring infrastructure can scale to the next order of magnitude
Dig deep to resolve complex issues
Continuously improve automation to reduce manual work
Improve internal tooling and developer experience
Contribute to incident response, postmortems, and the development of best practices around system reliability and scalability

Skills

Key technologies and capabilities for this role

Distributed SystemsDatabasesObservabilityCloud InfrastructurePerformance OptimizationAutomationIncident ResponsePostmortemsScalabilityReliability Engineering

Questions & Answers

Common questions about this position

What is the salary range for this Software Engineer position?

The salary range is $255K - $405K.

Is this a remote or on-site role?

This information is not specified in the job description.

What skills and experience are required for this role?

Candidates need 4+ years of relevant industry experience, with 2+ years leading large-scale projects or teams, deep understanding of distributed systems, experience with Kubernetes at scale, cloud platforms, Linux, Terraform, CI/CD, and observability stacks.

What is the team culture like at OpenAI's Infrastructure organization?

Teams operate with high autonomy and deep collaboration, sharing a mandate to improve safety, reliability, and velocity, with a humble attitude, eagerness to help colleagues, and commitment to team success.

What makes a strong candidate for this Infrastructure Reliability Engineer role?

Strong candidates own problems end-to-end, thrive in ambiguity and rapid change, have a track record in scalable systems, performance optimization, and cross-functional collaboration.

OpenAI

Develops safe and beneficial AI technologies

About OpenAI

OpenAI develops and deploys artificial intelligence technologies aimed at benefiting humanity. The company creates advanced AI models capable of performing various tasks, such as automating processes and enhancing creativity. OpenAI's products, like Sora, allow users to generate videos from text descriptions, showcasing the versatility of its AI applications. Unlike many competitors, OpenAI operates under a capped profit model, which limits the profits it can make and ensures that excess earnings are redistributed to maximize the social benefits of AI. This commitment to safety and ethical considerations is central to its mission of ensuring that artificial general intelligence (AGI) serves all of humanity.

San Francisco, CaliforniaHeadquarters

2015Year Founded

$18,433.2MTotal Funding

LATE_VCCompany Stage

AI & Machine LearningIndustries

1,001-5,000Employees

Benefits

Health insurance

Dental and vision insurance

Flexible spending account for healthcare and dependent care

Mental healthcare service

Fertility treatment coverage

401(k) with generous matching

20-week paid parental leave

Life insurance (complimentary)

AD&D insurance (complimentary)

Short-term/long-term disability insurance (complimentary)

Optional buy-up life insurance

Flexible work hours and unlimited paid time off (we encourage 4+ weeks per year)

Annual learning & development stipend

Regular team happy hours and outings

Daily catered lunch and dinner

Travel to domestic conferences

Risks

Elon Musk's legal battle may pose financial and reputational challenges for OpenAI.

Customizable ChatGPT personas could lead to privacy and ethical concerns.

Competitors like Anthropic raising capital may intensify market competition.

Differentiation

OpenAI's capped profit model prioritizes ethical AI development over unlimited profit.

OpenAI's AI models, like Sora, offer unique video creation from text descriptions.

OpenAI's focus on AGI aims to create AI systems smarter than humans.

Upsides

OpenAI's $6.6 billion funding boosts its AI research and computational capacity.

Customizable ChatGPT personas enhance user engagement and satisfaction.

OpenAI's 'Operator' AI agent could revolutionize workforce automation by 2025.

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