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Network Operations Engineer, Ai Networking

openai

San Francisco
AI

Job Score

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

About the Team

OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads.

About the Role

We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network.

The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil.

Key Responsibilities

  • Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers.

  • Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR).

  • Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks.

  • Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact.

  • Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance.

  • Support new AI cluster deployments, data center expansions, and infrastructure migrations in partnership with deployment and engineering teams.

  • Partner with cloud service providers (CSPs), colocation providers, Smart Hands teams, and hardware vendors to maintain production infrastructure.

  • Perform root-cause analysis (RCA) for production incidents and drive permanent corrective actions that eliminate recurring issues.

  • Build and maintain monitoring, telemetry, dashboards, and alerting to improve network observability and proactive issue detection.

  • Develop and improve operational runbooks, playbooks, troubleshooting documentation, and standard operating procedures.

  • Automate repetitive operational tasks using Python and infrastructure automation frameworks to reduce toil and improve efficiency.

  • Continuously identify opportunities to improve service reliability, scalability, operational maturity, and engineering efficiency.

Qualifications

  • Bachelor’s degree in Computer Science, Network Engineering, or a related discipline, or equivalent practical experience.

  • 5+ years of experience operating large-scale data center, cloud, AI, or HPC network infrastructure.

  • Experience supporting production network environments with high-availability requirements.

  • Hands-on experience with one or more of the following platforms: Cisco NX-OS, Arista EOS, NVIDIA Spectrum / Cumulus Linux, or Juniper JunOS.

  • Strong knowledge of Layer 2 and Layer 3 networking, BGP, OSPF, ECMP, MLAG, LACP, VRFs, and VLANs.

  • Experience troubleshooting physical infrastructure, including fiber optics, transceivers, DAC/AOC cables, and high-speed Ethernet links.

  • Experience performing software upgrades, hardware maintenance, and production change management.

  • Excellent analytical and troubleshooting skills, with the ability to communicate technical risk clearly across teams.

Preferred Skills

  • Experience operating AI or High-Performance Computing (HPC) network environments.

  • Experience with NVIDIA AI networking technologies and GPU infrastructure.

  • Experience supporting RoCE v2 or RDMA-based Ethernet fabrics, with a strong understanding of Priority Flow Control (PFC), Explicit Congestion Notification (ECN), Data Center Quantized Congestion Notification (DCQCN), Quality of Service (QoS), and lossless Ethernet networking.

  • Experience supporting 100G, 200G, 400G, and 800G Ethernet networks.

  • Experience with GPU platforms including NVIDIA HGX, DGX, GB200, or equivalent AI infrastructure.

  • Experience supporting distributed storage environments such as VAST, DDN, or similar technologies.

  • Experience working with cloud service providers such as AWS, Azure, or Google Cloud, and with third-party colocation providers.

  • Experience with network monitoring and telemetry technologies, including Prometheus, Grafana, gNMI, streaming telemetry, SNMP, or similar tools.

  • Experience developing automation using Python, Git, REST APIs, Terraform, or similar automation frameworks.

Work Environment and On-Call

  • Participate in a 24x7 on-call rotation supporting mission-critical AI infrastructure.

  • Support time-sensitive production incidents, maintenance windows, capacity expansions, and network changes with a focus on service availability and minimal customer impact.

  • This role requires up to 30% travel to data center locations for new turnups and acceptance activities, as needed.

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 Artificial Intelligence

Artificial Intelligence is currently the fastest-growing field in the technology market. The revolution in generative models (GPT, Claude, Gemini) has created massive demand for AI-specialized professionals.

Key areas of practice include Machine Learning Engineering, MLOps, Prompt Engineering, AI Research, and Applied AI. Python, TensorFlow, PyTorch, and LLM knowledge are essential skills.

AI salaries are the highest in the technology sector, with many remote work opportunities at international companies.

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Ecommerce Analysts in technology companies are highly valued, especially those who can turn buyer behavior data into actionable insights to increase revenue and reduce cart abandonment. The field offers opportunities from junior analyst to ecommerce analytics manager.

About Copywriting

The Copywriting area is responsible for creating persuasive, creative, and strategic texts for various communication channels. Copywriting professionals transform ideas into words that engage, convert, and build brand voice.

Key skills include advertising copywriting, script writing for videos and podcasts, persuasive writing, tone of voice, and editorial guidelines. Knowledge of SEO writing, Grammarly, and text productivity tools is a differentiator.

Copywriting professionals in technology companies are highly valued, especially those who master copy for landing pages, email sequences, and funnel content. The field offers opportunities from junior copywriter to head of copy, with a focus on creativity, persuasion, and performance.

About Business Intelligence

Business Intelligence (BI) is the area responsible for transforming raw data into strategic information for decision-making. BI professionals build dashboards, reports, and analyses that help companies understand their performance and identify growth opportunities.

Key skills include data modeling (star schema, snowflake), ETL (extraction, transformation, loading), advanced SQL, BI tools (Power BI, Tableau, Looker), data warehousing, KPIs, and business metrics analysis (MRR, churn, cohort). Knowledge of dbt, Airflow, and data pipelines is a differentiator.

BI professionals in technology companies are highly valued, especially those who master data visualization, analytics engineering, and can translate complex data into actionable insights for the business. The field offers opportunities from BI analyst to head of data, with a focus on data-driven decision making.

About Customer Success

Customer Success is the area responsible for ensuring clients achieve their goals when using the product or service. It is a strategic function for retention, expansion, and customer satisfaction.

Key skills include account management, churn analysis, NPS, onboarding, upsell, and cross-sell. Knowledge of CS tools like Gainsight, Totango, and ChurnZero is a differentiator.

CS is becoming increasingly strategic in SaaS companies, with professionals directly contributing to recurring revenue growth (MRR/ARR).

About UI Design

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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 2026 AI Boom: The Most Valuable Tech Careers and How to Land Six-Figure Remote Jobs

We are halfway through 2026, and one thing is crystal clear: the "experimental" phase of Artificial Intelligence is officially over. While 2023 and 2024 were characterized by awe over chatbots drafting emails and generating images, 2026 has solidified AI as the core infrastructure of global enterprises. The transition from standalone "AI tools" to Autonomous Agents and Multi-Agent Systems has radically transformed the job market.

For Tech, Design, and Digital Marketing professionals across the United States, 2026 represents the greatest window of opportunity of the decade to secure top-tier, 100% remote roles with highly lucrative six-figure compensations.

In this article, we will break down the current AI job landscape, backed by recent data, and list the top careers that startups and Fortune 500 companies are desperately trying to fill.

The Current Landscape: 2026 Data and Projections

The market isn't just hiring standard developers anymore; it's hiring intelligence orchestrators. According to recent Future of Work reports:

  • Exponential Growth: The World Economic Forum (WEF) 2026 update highlights that roles focused on AI, Machine Learning, and Big Data have grown by 45% compared to 2024, cementing them as the fastest-growing fields nationwide.
  • Corporate Adoption: Data published by Gartner earlier this year reveals that over 80% of Fortune 500 companies are now running Generative AI applications in production environments. This has created a massive demand for AI maintenance, ethics, and governance.
  • The Remote Premium: An internal analysis from Mondywork's database (which tracks integrations with major ATS platforms like Greenhouse and Ashby) shows that 73% of US-based AI roles are Remote-First. The average salary for senior specialists in these roles currently exceeds the $140,000 to $180,000 annual range, plus equity.

The 5 Hottest AI Opportunities in 2026

If you want to tailor your resume and LinkedIn profile to be easily captured by modern recruiting algorithms, these are the positions with the highest talent deficit in the US market right now:

1. MLOps and LLMOps Engineers (Operations Engineering)

Large Language Models (LLMs) are like Formula 1 engines: they need a full pit crew to avoid crashing on the track. The industry has realized that putting AI into production is vastly different from running a local model.

  • What they do: Manage infrastructure, oversee the model lifecycle, handle fine-tuning with proprietary company data, and ensure the AI does not suffer from large-scale hallucinations.
  • Hot Search Terms: MLOps, LLMOps, Platform Engineering, Data Ops, Kubernetes for AI.

2. Prompt Engineer & AI Interaction Designer

The profession many thought would be a passing fad has heavily evolved. The 2026 Prompt Engineer is not just someone who "talks well to machines"; they are complex logical system designers.

  • What they do: Sitting at the intersection of Software Engineering and UX Design, these professionals design system prompts for Autonomous Agents, build RAG (Retrieval-Augmented Generation) flows, and structure how AI safely interacts with end-users.
  • Hot Search Terms: Prompt Engineering, NLP, AI Behavior Design, UX Writer for AI.

3. Analytics Engineer / Structured Data Specialist

AI is completely useless without clean data. The classic Data Scientist role has yielded massive ground to the Analytics Engineer, the professional who bridges the gap between raw data engineering and business analysis.

  • What they do: Prepare, model, and transform chaotic data lakes into crystal-clear sources so enterprise AI models can consume data and generate real-time insights.
  • Hot Search Terms: Analytics Engineer, dbt, Snowflake, Computer Vision, BigQuery.

4. AI Product Manager (AI PM)

Companies are tired of building AI features "just because." Now, they need these features to drive serious revenue (ROI). The AI-focused Product Manager is the conductor of this orchestra.

  • What they do: Understand the technical limitations of modern LLMs, translate user pain points into viable AI solutions, and manage the product roadmap while ensuring the technology complies with strict privacy laws (like CCPA and GDPR).
  • Hot Search Terms: AI Product Manager, CPO, Product Ops, AI Governance.

5. AI Growth Marketer / High-Performance Media Buyer

In the digital marketing realm, 2026 is the year of autonomous campaign orchestration. Marketers still relying on 100% manual campaign creation are rapidly losing ground to those who can direct predictive AI.

  • What they do: Leverage Machine Learning and advanced AI tools for autonomous Conversion Rate Optimization (CRO), automated A/B testing, mass content generation, and predictive consumer behavior analysis.
  • Hot Search Terms: Growth Marketing, Media Buyer, Programmatic, AI Copywriting, Martech.

How to Prepare and Get Found (Beating the ATS Filters)

US companies utilize incredibly rigorous Applicant Tracking Systems (ATS) like Workday, Greenhouse, and Lever. They configure recruiting bots to filter resumes using fine-mesh keyword grids.

If you want to land these highly competitive roles, the golden rule is to mirror the exact industry jargon:

  • Don't just write "Data Analyst"; use "Data Ops" or "Analytics Engineer".
  • Don't just list "Cloud Support"; highlight "FinOps", "Cloud Architect", or "Platform Engineer".
  • Replace the outdated "Digital Marketer" with "Growth Ops" or "Performance Manager".

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Macroeconomic Reference Sources:

  • World Economic Forum - The Future of Jobs Report 2026 Update.
  • Gartner - Hype Cycle for Artificial Intelligence, 2026.
  • McKinsey Global Institute - The Economic Potential of Generative AI (Revisited 2026).