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Data Center Infrastructure Architect

openai

San Francisco
Data Uncategorized

Job Score

80 pts
On-site model (+70) Data (+10)

About the Team

OpenAI’s Industrial Compute team is building and productizing infrastructure capabilities that help organizations deploy and operate advanced AI systems at scale. The team works across AI hardware, systems engineering, physical infrastructure, and customer delivery to turn emerging technologies into reliable, repeatable infrastructure solutions.

Our work sits at the intersection of technical strategy, product development, engineering, and deployment. We partner closely with customers and internal engineering teams to solve complex infrastructure challenges spanning compute, power, cooling, controls, and facility efficiency.

About the Role

We are seeking a senior, hands-on Data Center Infrastructure Architect to develop and optimize the physical infrastructure required for large-scale AI deployments.

This is a broad technical role spanning data center architecture, electrical and mechanical systems, high-density compute, controls, telemetry, and digital modeling. You will use simulation, operational data, and digital-twin approaches to evaluate infrastructure designs, identify system-level constraints, and improve efficiency, reliability, cost, and speed of deployment.

The ideal candidate can move fluidly between first-principles analysis, facility and equipment design, computational modeling, engineering review, and real-world implementation. You should be comfortable working across disciplines rather than operating solely within electrical, mechanical, or software boundaries.

Key Responsibilities

  • Define system-level architectures for high-density AI data centers across power, cooling, IT equipment, controls, and facility infrastructure.

  • Develop digital twins and other computational models that represent the behavior of data center systems under changing workloads, environmental conditions, equipment configurations, and failure scenarios.

  • Use design and operational data to identify constraints, improve PUE and related efficiency metrics, and optimize capacity, reliability, water consumption, cost, and deployment schedules.

  • Evaluate tradeoffs across electrical topology, cooling architecture, rack density, redundancy, controls, maintainability, constructability, and operational complexity.

  • Translate evolving AI hardware requirements into practical facility, rack, power, and thermal architectures.

  • Establish reference architectures, modeling standards, design assumptions, performance requirements, and validation methodologies that can be reused across customer deployments.

  • Partner with software, data, controls, hardware, mechanical, electrical, construction, commissioning, and operations teams to connect digital models with real infrastructure behavior.

  • Integrate telemetry from systems such as BMS, EPMS, DCIM, SCADA, equipment controllers, and IT hardware into modeling and optimization workflows.

  • Lead technical reviews of customer and partner designs, identify material risks, and recommend changes grounded in quantitative analysis.

  • Work with customers and delivery teams to adapt reference solutions to site-specific constraints while preserving performance, reliability, and efficiency objectives.

  • Support pilots, commissioning, performance testing, and post-deployment analysis to validate models and continuously improve infrastructure designs.

  • Help shape the technical roadmap for Industrial Compute’s physical-infrastructure products and engineering services.

Qualifications

  • Significant experience designing or optimizing hyperscale data centers, large mission-critical facilities, or comparable infrastructure systems.

  • Broad knowledge of data center electrical and mechanical systems, including power distribution, backup power, thermal management, liquid cooling, heat rejection, controls, and monitoring.

  • Experience making system-level design decisions across multiple engineering disciplines.

  • Experience developing or applying simulation, optimization, digital-twin, or physics-based modeling techniques to physical infrastructure.

  • Strong understanding of data center efficiency and performance metrics, including PUE, WUE, utilization, capacity, reliability, and total cost of ownership.

  • Experience working with operational telemetry and translating real-world system behavior into design improvements.

  • Ability to evaluate complex tradeoffs involving performance, reliability, cost, schedule, scalability, sustainability, and maintainability.

  • Demonstrated ability to lead technical work in ambiguous, rapidly changing environments.

  • Strong written and verbal communication skills, including the ability to explain complex engineering decisions to customers, executives, and cross-functional teams.

  • Bachelor’s degree in mechanical engineering, electrical engineering, systems engineering, applied physics, or a related technical discipline.

Preferred Skills

  • Experience with high-density GPU clusters and direct-to-chip liquid cooling.

  • Experience connecting facility models with workload, rack, server, or chip-level power and thermal behavior.

  • Familiarity with modeling or engineering tools such as Modelica, MATLAB/Simulink, Python, EnergyPlus, computational fluid dynamics tools, or equivalent platforms.

  • Experience with BMS, EPMS, DCIM, SCADA, PLCs, data historians, or industrial controls.

  • Experience developing reference designs or new infrastructure architectures within a hyperscaler, data center operator, advanced engineering organization, or major design consultancy.

  • Experience taking an infrastructure concept from modeling and prototype validation through deployment and operational feedback.

  • Advanced degree in an engineering or scientific discipline.

Success in the First Year

  • Establish a credible system-level model of power, cooling, compute, and facility behavior for priority Industrial Compute use cases.

  • Identify and validate meaningful opportunities to improve efficiency, capacity, reliability, or deployment cost.

  • Deliver reusable reference architectures and engineering methodologies for customer deployments.

  • Create a repeatable feedback loop connecting modeling, operational telemetry, commissioning results, and future design decisions.

  • Become a trusted technical partner to internal engineering teams, customers, and infrastructure delivery 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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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.

Discover Other Areas

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

About Project Management

Project Management is essential to ensure strategic initiatives are delivered on time, within scope, and with quality. PM professionals coordinate teams, manage risks, and communicate with stakeholders.

Key methodologies include PMBOK, PRINCE2, Scrum, and Kanban. Tools like Jira, Asana, Monday, and MS Project are widely used in daily work.

Certifications like PMP and PgMP are important differentiators in the market, with growing demand in technology and consulting companies.

About Finance

The Finance area in technology companies combines traditional financial knowledge with advanced digital tools. FP&A, controlling, and corporate finance professionals are essential for the organization's financial health.

Key skills include financial modeling, metrics analysis (MRR, ARR, LTV, CAC), ERP (SAP, Oracle), and BI tools. Certifications like CFA and CPA-20 are differentiators.

The financial sector offers stable opportunities with competitive salaries, especially in fintechs and large technology companies.

About Technical Support

Technical Support is essential to ensure customer satisfaction and retention. Support professionals resolve technical issues, document solutions, and identify patterns that can lead to product improvements.

Key skills include troubleshooting, customer service, technical documentation, ITIL knowledge, and ticketing tools (Zendesk, Freshdesk, Intercom).

Technical support has evolved from a reactive to a proactive function, with high-level professionals working in Customer Engineering and Support Engineering.

About Talent Acquisition

Talent Acquisition is the strategic area responsible for attracting, selecting, and hiring the best professionals for the organization. Unlike traditional recruitment, TA acts as a strategic business partner, aligning talent acquisition with the company's long-term objectives.

Key skills include advanced sourcing, employer branding, labor market analysis, talent pipeline management, and candidate experience. Tools like LinkedIn Recruiter, ATS (Greenhouse, Lever, Ashby), and assessment platforms are essential.

TA professionals in technology companies are highly valued, especially those who master tech sourcing, workforce planning, and recruitment metrics like time-to-hire and cost-per-hire.

About Traffic Analyst

The Traffic Analyst (paid media/performance specialist) is the professional responsible for creating, managing, and optimizing sponsored ad campaigns on digital platforms such as Google Ads, Meta Ads, LinkedIn Ads, and TikTok Ads. They monitor conversion metrics, analyze return on investment (ROAS), perform A/B testing on ads and landing pages, and manage the marketing budget to maximize lead generation and qualified sales.

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.

Read full guide →

Finance Career Guide

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

Read full guide →

Communication Career Guide

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

Read full guide →

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.

Read full guide →

Product Career Guide

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

Read full guide →

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

Landing Top-Tier Traffic Analyst and SEO Roles

The New Era of Performance Marketing

The digital marketing landscape has undergone a radical transformation in recent years. The era of the "button pusher" who merely launched Meta Ads campaigns or stuffed keywords into WordPress is officially over. Today, companies—especially top-tier US startups and global tech corporations offering six-figure compensations—are looking for analytical, Growth-focused, and highly Data-Driven professionals.

Whether managing multi-million dollar paid media budgets or optimizing site architecture for the new AI-driven search engines, the Traffic and SEO Analyst has become the engine of predictable revenue for tech companies worldwide.

1. Technical SEO and the AI Revolution (SGE)

With Google's introduction of the Search Generative Experience (SGE), SEO is no longer just about backlinks and search volume. It now requires a deep understanding of search intent and topical authority.

What Tech Recruiters are looking for:

  • Technical SEO Mastery: The ability to analyze Core Web Vitals, manage Crawl Budgets, and optimize JavaScript rendering (a critical factor for modern frameworks like React and Next.js).
  • Advanced Data Analysis: Fluency in enterprise tools such as Screaming Frog, Semrush, Ahrefs, and Google Search Console.
  • Focus on E-E-A-T: Experience, Expertise, Authoritativeness, and Trustworthiness. Understanding how to structure content so that Google's algorithm recognizes it as a reliable primary source.
"Modern SEO success requires you to stop optimizing for algorithms and start optimizing for the user journey, using technical data to remove any friction along the way." — Google Search Central Guidelines

2. Paid Traffic: From Operational to Strategic

In the realm of paid media (Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads), platform automation handles most of the bidding work (Smart Bidding). The modern candidate's competitive edge lies in acquisition strategy and financial viability analysis.

Metrics you must master for your interviews:

  1. CAC (Customer Acquisition Cost): Moving beyond Cost Per Click (CPC). Understanding exactly how much it costs to acquire a paying user.
  2. LTV (Lifetime Value): Knowing how to cross-reference acquisition costs with the value a customer brings to the company over time (LTV:CAC ratio).
  3. ROAS vs. ROI: Grasping the crucial difference between the direct return on ad spend (ROAS) and the actual return on investment for the entire business (ROI).
  4. Server-Side Tracking: With the deprecation of third-party cookies, mastering the Conversions API and Google Tag Manager (GTM) Server-Side is a massive senior requirement.

3. Building an Unbeatable Portfolio

In the global remote market, degrees matter far less than proven results. Your portfolio shouldn't just be a resume; it should be a comprehensive document of Case Studies.

Structure your cases using the STAR method:

  • Situation: What was the baseline? E.g., "The e-commerce brand was burning $10k/month with a 1.2 ROAS."
  • Task: What was the goal? E.g., "Reduce CPA by 30% and increase non-branded organic traffic."
  • Action: What did YOU do technically? E.g., "Audited GTM, restructured PMax campaigns, and applied Schema markup in the HTML."
  • Result: The numerical impact. E.g., "Scaled ROAS to 3.8 and grew organic traffic by 45% in 3 months."

4. Certifications That Actually Open Doors

If you want to bypass strict Applicant Tracking Systems (ATS) like Greenhouse or Workday, ensure your LinkedIn and resume feature official certifications issued by the tech platforms themselves:

References and Must-Reads

To stay relevant in a market that changes weekly, we highly recommend following these official sources:

  1. Official Google Search Central Documentation.
  2. Annual State of Marketing Reports from HubSpot and Semrush.
  3. Technical articles focused on Data-Driven Marketing from the Harvard Business Review.

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