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Systems Generalist, Gpt Infrastructure

openai

Híbrido San Francisco
Uncategorized

Job Score

80 pts
Hybrid model (+80)

About OpenAI

OpenAI is dedicated to ensuring that artificial general intelligence (AGI) benefits all of humanity. Our mission requires building not only world-class AI models, but also the infrastructure that enables those models to be deployed reliably, efficiently, and at global scale. As demand for AI continues to grow, we are expanding the ways OpenAI can bring high-performance inference capacity online across a diverse hardware ecosystem.

About the Team

The GPT Infrastructure team builds software that turns advanced inference and optimization research into production products. One focus is enabling strategic infrastructure partners and accelerator vendors to qualify and onboard new compute without a bespoke porting and optimization effort for every hardware platform.

We build the control planes, APIs, secure partner-side execution environments, evaluation systems, artifact pipelines, and operational tooling that make these workflows repeatable and trustworthy. The work sits at the intersection of distributed systems, AI inference, compilers and runtimes, performance engineering, security, and external partnerships.

About the Role

We are seeking an experienced systems generalist who can work comfortably across the stack to help build an automated inference optimization platform. Given a workload, target hardware profile, compiler and runtime context, and a trusted verifier, the system runs durable optimization campaigns that generate, compile, execute, grade, and improve candidate kernels, runtime configurations, and serving-stack changes.

You will design both the OpenAI-hosted control plane and the partner-side software that evaluates candidates on real accelerator hardware. The product must keep long-running workflows reliable, make performance results reproducible, and maintain clear trust boundaries around sensitive model and hardware information.

This is a deeply cross-stack role, combining strong software engineering fundamentals with systems thinking and performance intuition. You will work closely with research, inference engineering, infrastructure, security, product, and strategic partners to turn a powerful research workflow into a scalable product.

Key Responsibilities

  • Design, build, and operate durable APIs and control-plane services for multi-hour or multi-day optimization campaigns, including scheduling, retries, budgets, checkpoints, artifact lineage, and observability.

  • Build secure partner-side runner and grader software that can compile, execute, verify, and benchmark candidate artifacts on third-party accelerator hardware.

  • Integrate hardware profiles, ISA and toolchain context, compilers, runtimes, and inference-serving engines into a repeatable optimization workflow.

  • Turn research prototypes into reliable product surfaces with clear contracts, debuggable failure modes, reproducible outputs, and excellent developer ergonomics.

  • Develop correctness and performance evaluation systems spanning latency, throughput, memory use, utilization, and cost efficiency.

  • Build artifact, provenance, and qualification workflows that make optimized kernels, binaries, configurations, and reports safe to review and deploy.

  • Collaborate with Research, Inference Engineering, Infrastructure, Security, Product, and Strategic Partnerships to deliver production-ready solutions.

  • Drive technical architecture and execution across ambiguous, cross-functional initiatives that connect OpenAI systems with partner environments.

Basic Qualifications

  • 8+ years of professional software engineering experience building large-scale distributed systems, infrastructure platforms, or cloud services, or equivalent depth of experience.

  • Strong programming skills in one or more of C++, Python, Go, or Rust.

  • Experience designing and operating highly available backend systems, APIs, job orchestration systems, or durable workflows for production workloads.

  • Strong understanding of distributed systems, Linux, networking, storage, containers, and modern cloud architectures.

  • Experience debugging complex systems and using measurement, profiling, and benchmarks to guide engineering decisions.

  • Proven ability to lead complex technical initiatives as a senior individual contributor and work effectively across organizational boundaries.

Preferred Skills

  • Experience with AI infrastructure, inference-serving systems, or large-scale machine learning systems.

  • Experience with compilers, runtimes, kernel optimization, or performance engineering; familiarity with technologies such as LLVM, MLIR, Triton, CUDA, or ROCm is a plus.

  • Familiarity with GPUs, accelerators, hardware architecture, ISA concepts, or vendor toolchains.

  • Experience with inference-serving frameworks or engines such as vLLM, SGLang, Triton Inference Server, or similar systems.

  • Experience building developer platforms, external APIs, remote execution systems, or secure partner-facing infrastructure.

  • Experience working with strategic cloud, hardware, or infrastructure partners.

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.

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Discover Other Areas

Understand the scope of work, key skills, and tools used in different career areas.

About Marketing

The Marketing area is strategic for the growth and positioning of any company. It encompasses traditional marketing, brand management, market research, trade marketing, product marketing, and market intelligence. Marketing professionals are responsible for planning and executing strategies that connect brands to their target audience.

Key skills include brand management, market research, competitive analysis, product marketing, trade marketing, pricing, relationship marketing, and channel development. Knowledge of research tools (Nielsen, Kantar, Ipsos), BI, and advanced spreadsheets is a differentiator.

Marketing professionals in technology companies are highly valued, especially those who master product marketing, go-to-market strategy, and data-driven marketing. The field offers opportunities from analyst to CMO, with a focus on growth, brand positioning, and return on investment.

About Backend

The Backend area is responsible for all server logic, APIs, databases, and infrastructure that support web and mobile applications. Backend professionals ensure that systems are scalable, secure, and performant.

Key skills include languages like PHP, Java, Python, Ruby, Go, and Node.js, frameworks like Laravel, Spring Boot, Django, and Express, databases (MySQL, PostgreSQL, MongoDB, Redis), software architecture (clean architecture, DDD, microservices), and API security (OAuth, JWT).

Backend developers in technology companies are highly valued, especially those who master microservices architecture, cloud computing, and high-scale performance. The field offers opportunities from junior developer to software architect, with a focus on scalability, security, and efficiency.

About Design

The Design field, especially UX/UI and Product Design, has experienced significant growth in recent years. With accelerated business digitization, the demand for professionals who can create intuitive and pleasant digital experiences has never been higher.

Key skills include Figma, Sketch, Adobe XD, user research, design thinking, prototyping, and system design. Product designers are increasingly valued for their direct impact on business results.

Remote work has opened doors for Brazilian designers to work for global companies, with competitive salaries in dollars and euros.

About Data

The Data field has undergone a radical transformation with the rise of Generative AI. Data professionals are fundamental for evidence-based decision-making across all industries.

Key specializations include Data Engineering, Data Science, Business Intelligence, Machine Learning Engineering, and Analytics. Tools like SQL, Python, Spark, dbt, and cloud platforms (AWS, GCP, Azure) are essential.

The data market continues with high demand and salaries among the most competitive in the technology sector, with many remote work opportunities.

About Branding

Branding is the area responsible for building, managing, and strengthening a brand's identity and market value. Branding professionals create strategies that define how the brand is perceived by the public, from the logo to the complete customer experience.

Key skills include brand strategy, visual identity, brand guidelines, positioning, naming, brand voice, market research, brand equity, and brand management. Knowledge of graphic design (Figma, Illustrator, Photoshop), storytelling, and brand experience is a differentiator.

Branding professionals in technology companies are highly valued, especially those who master employer branding, digital branding, and can build strong, memorable brands in competitive markets. The field offers opportunities from brand designer to head of brand, with a focus on identity, differentiation, and perceived value.

Career Guides

Technology Career Guide

Planning, skills, interviews, and professional growth in IT, Data Science, DevOps, and Product.

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Design Career Guide

UX/UI, Graphic Design, Product Design. Portfolio, tools, interviews, and growth in the Design field.

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Marketing Career Guide

SEO, Paid Media, Growth, Content Marketing. Certifications, tools, and strategies to grow in Digital Marketing.

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Finance Career Guide

Financial market, investments, corporate finance, certifications, and strategies to grow in the financial field.

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Communication Career Guide

Journalism, PR, Corporate Communication, Content Marketing, and Multimedia Production.

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Administration Career Guide

Business Management, HR, Logistics, Consulting, Project Management, and Entrepreneurship.

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Data Career Guide

Data Science, Data Engineering, BI, Machine Learning, and AI. From training to the job market.

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Product Career Guide

Product Management, Product Ownership, Agile, Scrum, and OKRs. From strategy to execution.

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Tech & Remote Glossary

Stop getting lost in interviews and job descriptions

The job market, especially within tech and global companies, has developed its own dialect. Not understanding these acronyms can make you lose valuable opportunities or poorly negotiate your contract. To end this problem, we created the Definitive Glossary for the Remote Professional.

🏢 Work Models & Routine

Async (Asynchronous Work)
A communication model where responses don't need to be immediate. Instead of back-to-back meetings, the team relies on well-structured documents, threads, and messages. It's the gold standard for global companies spanning multiple time zones.
Sync (Synchronous Work)
The opposite of Async. It requires the team to be online and available at the same time for meetings, live chats, and real-time collaboration.
Daily / Stand-up
A quick daily meeting (usually 15 minutes) common in Agile (Scrum) methodologies. The team answers three questions: What did I do yesterday? What will I do today? Are there any blockers?
All-Hands / Town Hall
A company-wide meeting involving all employees. Usually led by the founders (C-Levels) to present results, new goals, and answer team questions.
1:1 (One-on-One)
A recurring individual meeting between a professional and their direct manager. It is used for career alignment, feedback, and problem-solving, not just for project status updates.

💰 Contracts, Benefits & Compensation

PTO (Paid Time Off)
Instead of strict, categorized leave policies, modern US companies usually offer a flexible pool of days (e.g., 20 days of PTO, or even "Unlimited PTO") that you can use for vacations, sick days, or personal matters, while receiving your regular compensation.
Equity / Stock Options
Company ownership. The startup offers you the right to buy shares at a heavily discounted strike price in the future. If the company grows, goes public, or is acquired, these shares can be highly lucrative.
Vesting (Vesting Schedule)
The rule that controls your Equity. It usually lasts 4 years. You don't get all the shares on day one; you "earn" them gradually as you stay with the company. A "1-year Cliff" means you must stay for at least one year to receive your first batch of shares.
RSUs (Restricted Stock Units)
Unlike Stock Options (where you have the right to buy the stock), RSUs are actual shares the company grants you as a bonus or part of your compensation package, following a strict Vesting schedule.
Independent Contractor (1099 / B2B)
The most common international hiring model for global talent working for US companies. You act as a service provider (business-to-business), receiving the gross salary (often six-figure compensation) without standard local payroll tax deductions at the source.

🤖 Recruitment & Hiring Process

ATS (Applicant Tracking System)
The "robot" that reads your resume. Software like Greenhouse, Ashby, and Workday are used to filter candidates by keywords before a human even looks at the document. (Pro tip: this is why your resume must be clean, semantic, and have the right keywords).
JD (Job Description)
The document that lists the responsibilities, technical requirements, and benefits of the open position.
Cultural Fit
The interview stage that evaluates if your core values, communication style, and worldview align with the company's culture. This is the ultimate test of your Soft Skills.
Onboarding
The integration process. It's the period of your first few weeks at the company, where you get your access credentials, learn about the culture, study the internal documentation, and understand how the product works.

🚀 How to use this to your advantage?

The secret isn't just knowing what these acronyms mean, but using them actively. If during an interview for a premium tech role you ask, "How does your PTO policy and Vesting schedule work?", the recruiter will immediately perceive you as a high-level professional, familiar with the global market standards.

The remote job market requires preparation. And having the right vocabulary is the first big step to securing six-figure proposals and standing out among thousands of applicants.

Expert Tip

The Evolution of Support and Customer Success

The Evolution of Support and Customer Success: Opportunities, Tools, and the New Professional Profile

Discover how customer service evolved from a cost center into the ultimate growth and retention engine for the world's leading tech and SaaS companies.

The Current Landscape: From Cost Center to Revenue Engine

Historically, customer support was viewed by companies merely as a reactive department, focused on troubleshooting technical issues and closing tickets. However, with the consolidation of the SaaS (Software as a Service) business model and the subscription economy, the game has drastically changed.

Today, Customer Experience (CX) and Customer Success (CS) are the pillars of a company's financial sustainability. The logic is simple: in a highly competitive market, the Customer Acquisition Cost (CAC) is incredibly high. Losing a customer (Churn) means bleeding money. The modern support professional is, in reality, a strategist focused on retention, account expansion (Upsell/Cross-sell), and ensuring that the client achieves their desired outcomes using the product.

"Acquiring a new customer is anywhere from five to 25 times more expensive than retaining an existing one." — Harvard Business Review

Customer Support vs. Customer Success: Understanding the Difference

Although both areas walk hand-in-hand, their roles and success metrics in the job market are distinct. Understanding this difference is crucial for anyone looking to enter or advance in this career:

  • Customer Support: Predominantly reactive and transactional. The focus is on the speed and efficiency of issue resolution. Common metrics include First Response Time (FRT), Mean Time to Resolution (MTTR), and Customer Satisfaction Score (CSAT).
  • Customer Success: A proactive and long-term function. The goal is to ensure the customer extracts maximum value from the product. CS professionals analyze the Health Score, conduct Quarterly Business Reviews (QBRs), and directly target Net Retention Revenue (NRR) while combating Churn.

Market Opportunities and Global Remote Work

The global market for B2B Support and CS professionals is hotter than ever. Startups and major international corporations are massively hiring talent worldwide to provide 24/7 coverage across different time zones.

Opportunities range from entry-level roles, such as Customer Support Representative (CSR), to high-level executive positions like Key Account Manager, Implementation Specialist, Customer Success Manager (CSM), and Head of CX. For professionals with native or fluent English, "Global Remote" and "US Remote" positions offer highly competitive six-figure compensation packages, equity, and aggressive benefits.

Tech Stack: The Tools You Must Master

To pass through the rigorous ATS (Applicant Tracking Systems, like Greenhouse or Ashby) used by top-tier tech companies, your resume must showcase familiarity with the platforms that orchestrate the customer journey. The most demanded tools include:

  • Zendesk and Intercom: The global leaders in ticket management, asynchronous chat, and omnichannel support automation.
  • Salesforce and HubSpot: Essential CRMs (Customer Relationship Management) to maintain data history and alignment between Sales and Support teams.
  • Jira and Confluence: Atlassian tools crucial for escalating frontline bugs directly to the Engineering and Product teams.
  • Gainsight and Totango: Enterprise-grade platforms specifically built for Customer Success, used to monitor portfolio health predictively.

The Profile of the Modern CX Professional

The stereotype of the agent reading from a rigid script is a thing of the past. Tech recruiters are looking for a profile that blends emotional intelligence with analytical (data-driven) capabilities. The most valued competencies today are:

  1. Empathy and Resilience: The ability to de-escalate frustrated clients and turn crises into loyalty-building opportunities.
  2. Flawless Asynchronous Communication: Especially in remote work environments, clarity in writing emails, documentation, and chat threads is non-negotiable.
  3. Data Literacy: Knowing how to read dashboards, spot where users are getting stuck in the product, and suggest improvements based on hard data.
  4. Product Vision: Modern support acts as the primary feedback loop between the end-user and the Engineering and UX Design teams.