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Applied Ai Architect, Partner

openai

Híbrido Tokyo, Japan
AI

Job Score

90 pts
Hybrid model (+80) AI (+10)

About the Team

The AI Architect team partners with organizations to turn OpenAI's most capable models into meaningful, real-world impact. We work with customers across industries and digital-native businesses to identify where AI can create value, design secure and scalable solutions, and help those solutions move from early exploration into sustained production adoption. The team brings together technical strategy, customer partnership, and practical deployment expertise, working closely with Sales, Product, Engineering, Research, and specialist delivery teams.

Within the team, Partner Applied AI Architects work with strategic partners—including global and regional system integrators, consulting and advisory firms, and technology partners—to extend OpenAI’s technical reach and help partners deliver high-quality AI solutions for our joint customers. We bring together technical strategy, partner enablement, architecture expertise, and practical deployment experience, working closely with Partnerships, Sales, Product, Engineering, Research, Security, and specialist delivery teams.

About the Role

As a Partner Applied AI Architect, you will be a senior technical advisor to a portfolio of strategic partners and the primary technical counterpart to their leadership and delivery organizations. You will shape how partners build practices around OpenAI, develop solutions using our products, and take joint customers from AI opportunity and technical evaluation through production adoption and measurable business impact.

You will own the technical strategy and architecture across partner engagements involving ChatGPT Enterprise, the OpenAI API, Codex, and other agentic AI solutions. In close partnership with the Revenue Partnerships team, you will translate joint business priorities into technical strategies, solution patterns, enablement plans, and a focused portfolio of high-value customer opportunities.

You will work directly with partners on strategic customer engagements—leading discovery, shaping architectures, navigating complex technical decisions, and helping secure technical wins—while building the partner capabilities required to deliver successfully and independently at scale.

You will remain accountable for the technical quality and outcomes of the partnership while bringing in the right specialists across deployment, implementation, security, product, enablement, and other teams when deeper expertise is needed. The role calls for strong architectural judgment, executive presence, partner leadership, and the ability to move confidently between business strategy and hands-on technical conversations.

In this role, you will:

  • Serve as the primary technical advisor and long-term technical relationship owner for a portfolio of strategic partners, building trusted relationships with their executives, AI leaders, architects, engineering teams, and delivery organizations.

  • Partner closely with the Revenue Partnerships team as one virtual team, aligning partner strategy, technical priorities, joint customer opportunities, and measures of success.

  • Develop the technical strategy and plan for each partner, identifying priority solutions, use cases, technical capabilities, enablement needs, delivery risks, and opportunities to drive customer adoption.

  • Assess prospective and existing partners’ technical capabilities and delivery readiness, identifying strengths, gaps, and the investments required to successfully deliver OpenAI-powered solutions.

  • Lead technical discovery with partners and joint customers to identify, qualify, and prioritize AI use cases tied to meaningful business outcomes.

  • Develop clear Applied AI architectures spanning models, applications, enterprise data, integrations, identity, security, privacy, governance, evaluation, reliability, and deployment.

  • Collaborate with partner sales and technical teams on strategic opportunities, providing technical guidance through discovery, demonstrations, workshops, prototypes, architectural recommendations, and proofs of value.

  • Guide partners through their initial and most strategic OpenAI deployments, helping them navigate technical tradeoffs and production dependencies while ensuring solutions meet a high bar for quality, security, reliability, and responsible deployment.

  • Build partner capability and technical self-sufficiency through tailored enablement, architectural guidance, reusable solution patterns, technical workshops, and mentorship.

  • Establish clear standards and mechanisms for partner-delivered solution quality, identifying risks early and intervening when architecture, implementation, security, evaluation, or adoption issues threaten customer outcomes.

  • Orchestrate the right OpenAI specialists across Deployment Engineering, Product, Security, implementation, enablement, and domain teams while maintaining clear ownership and handoffs between OpenAI and partner delivery teams.

  • Track partner capability, joint pipeline technical progress, production adoption, usage, solution quality, and measurable customer impact to identify where additional investment or intervention is needed.

  • Identify repeatable patterns across partner engagements and turn them into architectures, playbooks, reference solutions, and best practices that allow successful approaches to scale across partners and customers.

  • Bring insights from partners and joint customers back to Product, Engineering, Research, and Partnerships, helping shape product strategy, technical guidance, and the broader OpenAI partner ecosystem.

You might thrive in this role if you:

  • Have significant experience in senior customer- or partner-facing technical roles such as solutions architecture, partner engineering, field architecture, technical account leadership, AI deployment, or technical consulting.

  • Have worked successfully with global or regional system integrators, consulting firms, or other technology partners, and understand how partner organizations sell, architect, and deliver complex enterprise technology.

  • Have guided complex enterprise organizations from technical discovery and evaluation through production deployment, adoption, and measurable business impact.

  • Can build credibility with CTOs, CIOs, CISOs, partner executives, and AI leaders while communicating equally effectively with architects and hands-on engineers.

  • Bring strong software and cloud architecture foundations, including APIs, distributed systems, enterprise data, integrations, identity, security, privacy, and governance.

  • Understand modern AI systems, frontier LLMs, agentic applications, model evaluation, retrieval, and enterprise AI workflows.

  • Can prototype when useful, explain technical tradeoffs clearly, and work confidently with APIs, SDKs, and languages such as Python or JavaScript.

  • Have experience enabling technical organizations at scale, turning your own expertise into repeatable architectures, training, patterns, and practices that others can successfully apply.

  • Understand enterprise security and compliance requirements and can guide partners and customers through the technical considerations required to move AI systems safely into production.

  • Are comfortable balancing the needs of OpenAI, the partner, and the end customer, and can exercise sound judgment when those priorities do not perfectly align.

  • Know when to go deep personally, when to coach a partner toward the answer, and when to engage specialist resources.

  • Can prioritize across a portfolio of partners and customer opportunities, focusing technical resources on the work most likely to create durable customer value and adoption.

  • Communicate clearly and can turn ambiguity into a practical architecture, executive decision, enablement plan, or path to production.

  • Own problems end-to-end, learn quickly, and care deeply about helping partners and customers deploy advanced AI responsibly.

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.

Discover Other Areas

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

About Web Designer

The Web Designer is the professional responsible for creating visual interfaces for websites, web applications, and landing pages, combining aesthetics, usability, and user experience. They transform business needs into functional and responsive layouts that communicate brand identity.

Key skills include UI design, responsive design, prototyping (Figma, Sketch, Adobe XD), wireframing, design systems, accessibility (WCAG), information architecture, and basic HTML/CSS knowledge. Knowledge of UX design, motion design, and front-end is a differentiator.

Web Designers in technology companies are highly valued, especially those who master design systems, design tokens, and can create interfaces that convert and engage. The field offers opportunities from junior web designer to product designer and design lead.

About Automation Analyst

The Automation Analyst is the professional responsible for identifying process optimization opportunities and developing automated workflows (RPA, scripts, or integrations). They map manual and repetitive tasks across various company areas and build automation solutions using low-code/no-code platforms (such as Zapier, Make, Power Automate, n8n) or RPA tools (such as UiPath), driving operational efficiency and error reduction.

About Content Writer

The Content Writer is the professional responsible for creating quality written content for websites, blogs, social media, and other digital platforms. They combine writing skills with content strategy and SEO to attract, engage, and convert audiences.

Key skills include blog content creation, landing pages, newsletters, social media content, keyword research, content strategy, editorial calendar, and SEO writing. Knowledge of WordPress, Surfer SEO, Ahrefs, and analytics tools is a differentiator.

Content Writers in technology companies are highly valued, especially those who can create accessible technical content, evergreen content, and content that generates organic traffic. The field offers opportunities from junior content writer to head of content, with a focus on quality, strategy, and content performance.

About UX Design

The User Experience (UX) Design area focuses on optimizing the overall user experience when interacting with a product or service. UX professionals conduct user research (UX Research), map journeys, create wireframes, perform usability tests, and define navigation flows to ensure the product is intuitive, useful, and meets users' real needs.

About QA and Testing

QA and Software Testing are fundamental to ensure the quality and reliability of applications. QA professionals ensure that the delivered product meets requirements and is free of critical defects.

Key skills include manual and automated testing, Selenium, Cypress, Playwright, Postman, JMeter, and CI/CD pipeline knowledge. Performance and security testing are differentiators.

With the adoption of DevOps and continuous deployment, the demand for automation QAs and SDETs continues to grow.

Career Guides

Technology Career Guide

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

Read full guide →

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 Current State of the Cloud & DevOps Market

By Mondywork | The ultimate guide for tech professionals looking to level up their careers, land global remote roles, and master modern infrastructure.

The End of the "SysAdmin" and the Rise of Platform Engineering

If you've been tracking the most sought-after roles at startups and Fortune 500 companies, you've probably noticed a drastic shift. The Cloud Computing and DevOps market is no longer just about "keeping the app online." Today, companies demand extreme resilience, automation, and cost optimization (the famous FinOps).

DevOps culture has evolved. We are now in the era of Platform Engineering, where infrastructure teams build internal platforms to grant developers full autonomy (Self-Service). For those aiming for global remote roles with six-figure compensation, understanding this transition isn't just a plus—it's a strict requirement.

"Elite DevOps teams deploy code 973 times more frequently and boast a Mean Time To Recovery (MTTR) that is 6,570 times faster than low-performing teams."

— State of DevOps Report (DORA / Google Cloud)

What Do Recruiters and ATS Systems Really Look For?

Automated filters (ATS platforms like Greenhouse, Ashby, and Workday) are hardwired to scan for a very specific set of skills in Cloud/DevOps resumes. Simply listing 20 tools won't cut it anymore; you must demonstrate culture and real-world impact.

  • Infrastructure as Code (IaC): Forget clicking around the AWS console. Declarative tools like Terraform, Pulumi, and Ansible are the true industry standards.
  • Container Orchestration: Mastery of Docker and, above all, Kubernetes (K8s) is practically mandatory for premium roles.
  • CI/CD Culture: Building automated pipelines (GitHub Actions, GitLab CI, ArgoCD) that guarantee continuous and secure deployments.
  • Cloud Providers and Architecture: Proficiency in at least one major public cloud provider (AWS, Google Cloud, or Microsoft Azure), with a strong focus on Serverless, microservices, and system resilience.

How to Transition: The Roadmap to Success

Many Back-End developers, support analysts, and network professionals want to pivot to Cloud and DevOps. If that's your goal, follow this market-validated roadmap:

  1. Master the Basics (Linux and Networking): Modern DevOps runs on Linux. Understanding permissions, processes, bash scripting, and the fundamentals of TCP/IP, DNS, and Load Balancers is your foundation.
  2. Learn to Code: A DevOps engineer doesn't need to be a Senior Developer, but you must know how to automate tasks. Python and Go (Golang) are currently the most highly valued languages in this ecosystem.
  3. Are Certifications Worth It? Yes, especially to get past the initial HR screening. Certifications like the AWS Certified Solutions Architect – Associate or the CKA (Certified Kubernetes Administrator) carry massive weight in the global market.
  4. Build a Real Portfolio: Publish a project on GitHub where you provision infrastructure via Terraform, set up a CI/CD pipeline using GitHub Actions, and deploy a simple app to a Kubernetes cluster. Practical projects always beat theoretical resumes.

Essential References and Study Links

To stay up-to-date, we highly recommend following official organizations and annual market reports:


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