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Applied Ai Architect, Education

openai

Híbrido London, UK
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 Education, we partner with universities, schools, research institutions, and countrywide education systems to advance responsible, mission-aligned uses of AI. These environments require more than technical deployment: success depends on institutional trust, thoughtful governance, stakeholder education, change management, and a value narrative that resonates with academic leaders, researchers, IT teams, faculty, administrators, and students.

This role is based in London. We use a hybrid work model of 3 days in the office per week and offer relocation assistance.

About the Role

As an Applied AI Architect for Education, you will be the senior technical owner for a named portfolio of education customers and the primary technical counterpart to their leadership teams. You will act as the “CTO of your book of business,” shaping each institution’s AI strategy and guiding its journey from pre-sales discovery and solution evaluation through deployment, adoption, and measurable institutional impact.

You will own the technical account plan across ChatGPT Edu, the OpenAI API, Codex, and other agentic AI solutions. In partnership with the Account Director, you will translate institutional priorities into a focused portfolio of use cases, an actionable adoption roadmap, and a clear path to durable value and growth. The Account Director owns the commercial strategy; you own the technical strategy, customer journey, and path to production value.

You will work across academic, research, administrative, and operational contexts—helping customers determine where AI can responsibly improve teaching and learning, accelerate research, strengthen student and faculty services, and make institutional operations more effective. You will account for the realities of education environments, including shared governance, complex stakeholder networks, academic calendars, accessibility, data privacy, responsible-AI expectations, and the need to build confidence among communities with differing levels of AI readiness.

You will remain accountable for the technical outcome while bringing in the right specialists across deployment, implementation, enablement, security, product, education programs, and partners. This role calls for strong education-sector fluency, sound architectural judgment, and the ability to move confidently between executive strategy, academic and operational workflows, and hands-on technical conversations.

In this role, you will:

  • Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of existing education customers and pre-sales prospects.

  • Partner with Account Directors on account strategy while owning the technical account plan, technical milestones, adoption priorities, value-realization path, and expansion opportunities.

  • Lead discovery with institutional executives, academic leaders, researchers, faculty, administrators, and technical teams to identify and prioritize use cases connected to meaningful institutional objectives.

  • Translate education priorities into clear Applied AI Architectures spanning models, applications, institutional data, identity, integrations, security, privacy, governance, evaluation, and deployment.

  • Guide institutions through technical evaluations, demonstrations, workshops, prototypes, and proofs of value, building confidence in both the solution and its responsible path to production.

  • Translate institutional objectives into actionable adoption roadmaps with clear workstreams, sequencing, milestones, stakeholder ownership, governance, risks, success measures, and change-management needs.

  • Develop a focused use-case portfolio across areas such as teaching and learning, research, student and faculty services, knowledge management, software development, and administrative operations.

  • Translate institutional objectives into actionable adoption roadmaps with clear workstreams, sequencing, milestones, stakeholder ownership, governance, risks, success measures, and change-management needs.

  • Build trusted relationships and technical champions across CIOs, CTOs, CISOs, provosts, deans, research leaders, faculty, administrators, and other institutional stakeholders.

  • Qualify and coordinate support from Deployment Engineering, implementation, training and enablement, Product, Research, education specialists, partners, and other delivery teams.

  • Remain accountable for technical progress and customer outcomes while ensuring delivery teams own implementation execution once engaged.

  • Track adoption, usage, account health, production readiness, and measurable customer impact, intervening early when risks threaten value realization.

  • Identify repeatable education patterns and reusable architectures that can accelerate responsible adoption across institutions, departments, campuses, and education systems.

  • Translate field insights into actionable feedback for Product, Engineering, and Research, representing the needs and production patterns of education customers.

  • Help identify expansion opportunities where OpenAI can support additional academic, research, administrative, or operational workflows.

You might thrive in this role if you:

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

  • Have guided complex organizations from technical evaluation through production adoption and measurable value realization.

  • Build credibility with senior technical and business leaders while communicating equally well with hands-on engineers.

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

  • Understand modern AI systems, frontier LLM models, agentic applications, model evaluation, retrieval, or enterprise AI workflows.

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

  • Exercise sound judgment about when to go deep personally, when to involve specialists, and how to define clear handoffs and ownership.

  • Have experience developing technical account plans, prioritizing complex customer portfolios, and connecting adoption to measurable outcomes.

  • Can translate technical capabilities into institutional value across priorities such as student success, research productivity, faculty enablement, administrative effectiveness, accessibility, risk, and governance.

  • Communicate clearly and can turn ambiguity, competing stakeholder needs, and complex technical choices into a practical narrative, executive decision, or action plan.

  • Work collaboratively across disciplines and care deeply about helping education institutions deploy advanced AI safely, responsibly, and in service of their missions.

  • Meaningful experience with education technology, higher education, K–12 systems, research institutions, or similarly mission-driven and consensus-oriented environments is an added bonus

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 Cloud Solutions

The Cloud Solutions area is responsible for designing, implementing, and managing cloud infrastructure and services (AWS, Azure, GCP) for companies. Cloud professionals architect scalable, secure, and cost-optimized solutions, from data center migrations to serverless and multi-cloud architectures.

Key skills include IaC (Terraform, CloudFormation), containers (Docker, Kubernetes), serverless (Lambda, Cloud Functions), managed databases (RDS, DynamoDB, BigQuery), cloud networking (VPC, CDN, load balancer), and security (IAM, WAF, KMS). Knowledge of FinOps, cloud governance, and AWS/Azure/GCP certifications is a differentiator.

Cloud Solutions professionals in technology companies are highly valued, especially those who master multi-cloud architectures, FinOps, and can optimize costs while maintaining performance and security. The field offers opportunities from cloud engineer to cloud solutions architect, head of cloud, and chief cloud architect.

About Systems Analyst

The Systems Analyst is the professional responsible for analyzing, designing, and implementing technology solutions that meet business needs. They act as a bridge between business areas and the development team, ensuring that systems deliver real value to the organization.

Key skills include requirements gathering and analysis, process modeling (BPMN), data modeling, technical and functional documentation, system integration (APIs, microservices), and knowledge of ERPs and CRMs. Tools like Jira, Confluence, Visio, and project management platforms are essential.

Systems Analysts in technology companies are highly valued, especially those who master agile requirements analysis (user stories, backlog), system integration, and solution architecture. The field offers opportunities from junior analyst to solution architect, with a focus on efficiency, quality, and technological innovation.

About Content Manager

The Content Manager is the professional responsible for leading the entire content strategy, production, and management of an organization. They define the editorial strategy, coordinate writing teams, and ensure content aligns with business goals and brand identity.

Key skills include content strategy, editorial planning, content audit, buyer persona, customer journey, content ops, content governance, performance metrics (ROI, engagement, organic traffic), and team management. Knowledge of WordPress, Contentful, Notion, and analytics tools is a differentiator.

Content Managers in technology companies are highly valued, especially those who can align content with conversion funnels, lead multidisciplinary teams, and use data to optimize editorial strategy. The field offers opportunities from content manager to head of content, with a focus on strategy, quality, and scale.

About Business Analysis

The Business Analyst (BA) is the professional responsible for identifying problems, opportunities, and solutions in organizational processes, acting as a bridge between business areas and the technology development team. They gather and specify requirements, map value streams, design future processes, and help ensure that software deliveries align with the company's strategic goals.

About People Analyst

The People Analyst is the professional responsible for transforming people data into strategic insights for HR decision-making. They combine data analysis knowledge with people management vision to help organizations understand workforce metrics, turnover, engagement, and diversity.

Key skills include people analytics, workforce analytics, turnover and retention analysis, HR metrics (time-to-hire, cost-per-hire, e-NPS), data visualization (Power BI, Tableau, Visier), workforce planning, and compensation analysis. Knowledge of statistics, SQL, and people analytics tools is a differentiator.

People Analysts in technology companies are highly valued, especially those who can translate complex people data into actionable insights for retention, diversity, and growth strategies. The field offers opportunities from HR analyst to head of people analytics, with a focus on data-driven people management.

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Finance Career Guide

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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 Back-End Development Market

The Back-End Development Market: Barriers, Opportunities, and the Path to the Top

Behind every brilliant application, revolutionary artificial intelligence, or successful fintech, there is an invisible and robust ecosystem. Welcome to the Back-End universe.

The Modern Back-End Paradox: Did AI Steal the Jobs?

With the rise of tools like GitHub Copilot and Cursor, many junior developers wonder if the Back-End career is threatened. The short answer is: no. In fact, it has evolved.

Artificial Intelligence has made writing basic "CRUD" (Create, Read, Update, Delete) code trivial. However, the market no longer pays six-figure salaries for writing repetitive code. The global market is actively hunting for Software Engineers—professionals who understand architecture, resilience, latency, and scalability. The Back-End didn't die; the bar was simply raised.

Barriers to Entry: What Separates Juniors from Seniors

Entering Back-End development today requires overcoming technical barriers that go far beyond mastering a programming language (like Java, C#, Go, or Python). Key barriers include:

  • System Design: Knowing how to design a system that supports 100 users is easy. Designing one that handles 1 million requests per second requires deep knowledge of load balancing, caching (Redis/Memcached), and message queues (RabbitMQ/Kafka).
  • Data Complexity: The debate is no longer just "SQL vs. NoSQL". It is about data modeling, replication, sharding, and how to avoid database bottlenecks in distributed systems.
  • Security: With data breaches costing millions, companies require developers to master security practices from day one. Not knowing the vulnerabilities listed by the OWASP Top 10 is a dealbreaker for premium remote roles.
  • DevOps and Cloud Culture: The modern Back-End developer must understand containerization (Docker), orchestration (Kubernetes), and cloud infrastructure (AWS, GCP, Azure).

Golden Opportunities: Where is the Money?

For those who overcome these barriers, the market is a blue ocean of opportunities, especially for US/Global Remote work.

  • Migration to Microservices and Serverless: Corporate giants continue to dismantle legacy monoliths. Professionals who understand the patterns described by Martin Fowler are highly sought after.
  • High-Performance Languages: While traditional languages maintain their corporate strength, the use of Go (Golang) and Rust has skyrocketed for systems requiring massive concurrency and low memory footprint (Green Computing).
  • AI Infrastructure: AI models don't run in a vacuum. There is a massive demand for Back-End engineers proficient in Python and C++ to build data pipelines (MLOps) and the APIs that serve these models in real time.

Success Stories: Architectural Decisions That Changed the Game

True Back-End engineering shines when solving impossible problems. Let's look at real-market examples:

The Discord Case (Migration to Rust): Discord faced latency spikes in its core Read States service, originally written in Go. Because Go's Garbage Collector caused critical millisecond freezes, the team rewrote the service in Rust, completely eliminating latency spikes and supporting trillions of messages with absurd efficiency. This proved the value of choosing the right tool for performance limits.

The Netflix Case (Pioneering Microservices): Netflix transformed a monolithic system that broke under pressure into an architecture of thousands of independently managed microservices. They pioneered the concept of Chaos Engineering, purposely shutting down production servers to ensure their Back-End was resilient to failure.

Practical Tips: How to Land Premium Global Jobs

  1. Master the Fundamentals: Before learning the trendy framework of the month, study data structures, algorithms, and time complexity (Big-O Notation). This is exactly what will be tested in high-level technical interviews (Whiteboard interviews).
  2. Build a Problem-Focused Portfolio: A GitHub repository with a "To-Do List" won't impress anyone. Build an API that handles asynchronous image processing, create a scalable URL shortener, or engineer a messaging system using WebSockets and Redis.
  3. Study Real Cloud Architecture: Get solutions-based certifications (like AWS Certified Developer or Solutions Architect). These serve as a "Seal of Approval" to bypass strict Applicant Tracking Systems (ATS) like Greenhouse or Ashby.
  4. Flawless Technical Communication: According to the Stack Overflow Developer Survey, the highest-paying roles require asynchronous global collaboration. Your code documentation, commit messages, and PR reviews must be pristine and professional.

Verdict: Is a Career in Back-End Worth It?

Absolutely. If you are an analytical person who loves solving complex puzzles and cares about the security and efficiency of things no one sees, the Back-End is your place.

It is a career virtually immune to visual fads. While Front-End libraries change every few years, the fundamentals of relational databases, networks, and operating systems remain the same. It is a rock-solid foundation for a highly lucrative and globalized career.