← Back to jobs

Applied Ai Engineer, Codex

openai

Híbrido London, UK
AI

Job Score

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

About the Team

OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. For software engineering organizations, this means helping customers adopt Codex and other OpenAI capabilities across the software development lifecycle—transforming how teams plan, build, test, review, and deliver software.

We work directly with engineering leaders and hands-on developers to identify high-value opportunities, design and implement AI-powered development workflows, and scale what works across engineering organizations. We turn lessons from these deployments into better products, reusable architectures, and technical patterns that help developers everywhere get more value from Codex.

About the Role

As an Applied AI Engineer focused on Codex, you will partner directly with leading engineering organizations to design, build, and deploy AI systems that transform how software is developed. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from workflow and use-case selection through prototyping, evaluation, production rollout, and scaled adoption.

You will work alongside engineering teams to build advanced AI coding workflows, integrations, automations, and evaluation systems—often using Codex itself as part of your development process. You will help customers make technical decisions involving model behavior, agentic workflows, developer environments, security, reliability, evaluation, and operational readiness, while ensuring deployments translate into measurable improvements in engineering productivity and software delivery.

You will work closely with OpenAI Product, Research, Engineering, Security, Sales, and the broader Codex organization, translating real-world deployment experience into high-signal product and model feedback. Success is measured by production systems, sustained developer adoption, and meaningful improvements to how engineering organizations build software—not simply successful demonstrations or enablement activity.

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

In this role, you will:

  • Partner directly with engineering leaders and hands-on developers to identify high-value opportunities for Codex and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria.

  • Design, build, and deploy AI-powered software development workflows that improve how engineering teams plan, write, test, review, debug, and deliver software.

  • Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, workflow automations, and production accelerators—often using Codex as part of your own development process.

  • Help customers progress from promising experiments to reliable production workflows, sustained developer adoption, and scaled impact across engineering organizations.

  • Design systematic approaches for evaluating AI coding systems using representative software engineering tasks, automated graders, production signals, and developer feedback.

  • Make sound technical decisions across models, agents, tools, developer environments, integrations, reliability, observability, latency, cost, safety, security, and operational readiness.

  • Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive technical blockers toward resolution.

  • Lead technical deep dives, workshops, and hands-on enablement that help engineering teams understand and adopt advanced AI coding workflows effectively and safely.

  • Gather high-fidelity insights from real-world Codex deployments and translate them into clear product proposals, model feedback, and technical requirements for OpenAI Product, Research, and Engineering teams.

  • Create reusable architectures, tooling, examples, guides, and technical patterns—including contributions to resources such as the OpenAI Cookbook—that accelerate future Codex deployments.

  • Influence customer engineering strategy by helping technical leaders understand how AI coding systems can reshape their software development lifecycle, engineering practices, and organizational workflows.

You’ll thrive in this role if you:

  • Have a demonstrated track record of designing, building, and delivering software or AI systems in enterprise environments, including taking systems from prototype to production. Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, developer tooling, customer engineering, solutions architecture, or technical consulting.

  • Can point to substantial personal contributions in code, architecture, evaluation, debugging, integrations, or production engineering—not only program, enablement, or stakeholder management.

  • Are highly proficient in Python and comfortable working across modern software development environments; experience with JavaScript, TypeScript, or another relevant language is valuable.

  • Are an active user of AI coding tools and have developed a strong point of view on how AI can improve developer productivity and software engineering workflows.

  • Enjoy building high-signal prototypes, integrations, automations, and production solutions that demonstrate and deliver what AI coding systems can enable.

  • Understand how to evaluate AI coding systems systematically, including designing representative tasks, automated evaluations, production signals, and mechanisms for incorporating developer feedback.

  • Have navigated enterprise production requirements such as developer tooling integrations, reliability, observability, security, privacy, data governance, performance, and cost.

  • Can connect technical decisions to developer workflows, adoption, engineering productivity, and measurable business outcomes.

  • Communicate with clarity and credibility across hands-on engineers, engineering leaders, security teams, product leaders, and executives.

  • Are comfortable leading technical workshops and hands-on sessions that help engineering organizations adopt new development workflows and technologies.

  • Bring high agency, strong technical judgment, and end-to-end ownership in ambiguous and rapidly evolving environments.

  • Learn quickly, challenge assumptions constructively, and collaborate with humility; deep prior experience with OpenAI products is not required.

  • Are able to speak English fluently.

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.

What did you think of this job?

Comments 0

Want to leave a comment?
Sign in or create your account in seconds to join the discussion.
Loading comments...

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 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 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 Marketing

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

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

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

About Product Owner

The Product Owner (PO) is the professional responsible for maximizing the value of the product delivered by the development team. They act as the voice of the customer and stakeholders, managing and prioritizing the product backlog, defining clear user stories, and ensuring the team works on the most valuable items for the business.

Key skills include backlog management, user story writing, prioritization (Mascow, RICE), agile methodologies (Scrum, Kanban), and stakeholder communication. Knowledge of tools like Jira, Trello, Azure DevOps, and Miro is essential.

Product Owners are highly sought-after professionals in the technology market, working collaboratively with Scrum Masters, Product Managers, and engineering teams to drive agility and continuous value delivery.

About Product Manager

The Product Manager (PM) is the professional responsible for defining the strategy, vision, and roadmap of a digital product. They work at the intersection of technology, business, and user experience (UX), leading the discovery and delivery of solutions that solve real problems in a viable way for the company.

Key skills include product discovery, data and metrics analysis (AARRR, NPS, LTV), user research, go-to-market strategy, roadmapping, strategic prioritization, and leadership by influence. Tools like Amplitude, Mixpanel, Hotjar, Jira, and Notion are fundamental.

Product Managers play a central role in the growth of startups, scale-ups, and large technology companies, with career progression opportunities to Product Leader, Head of Product, and Chief Product Officer (CPO).

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.

Read full guide →

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.

Read full guide →

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

Data-Driven: How Data Defines Company Success or Failure

The Data-Driven Era: How Data Culture Defines Company Success or Failure

Published by Mondywork | Category: Data / Business Intelligence

The End of Corporate Gut Feeling

In the past, major business decisions were made based on intuition, previous experience, or the famous "gut feeling" of directors (what the market refers to as the HiPPO - Highest Paid Person's Opinion). Today, however, in a highly competitive and globalized corporate ecosystem, relying on guesswork is the fastest recipe for bankruptcy.

Digital transformation didn't just connect processes; it generated a massive volume of information. The companies that thrive are those that know how to capture, clean, and transform this raw data into actionable insights.

"Data-driven organizations are 23 times more likely to acquire customers, six times as likely to retain those customers, and 19 times as likely to be profitable as a result."
— McKinsey Global Institute Study

What Does it Mean to Have a Data-Driven Culture?

Being Data-Driven doesn't just mean subscribing to expensive Analytics tools or having a beautiful dashboard on the office wall. It's a fundamental shift in organizational culture, where truth is sought in the numbers before any action is executed.

  • Predictability: Predictive models allow companies to forecast market trends, customer churn, and operational bottlenecks before they happen.
  • Risk Mitigation: Decisions based on statistics drastically reduce the margin of error in investments and new product launches.
  • Personalization at Scale: Behavioral analysis enables marketing to deliver exactly what the user wants, right when they have the highest propensity to buy.

The Impact of Business Intelligence (BI) and Big Data

To extract the true value from information, companies are building robust Business Intelligence (BI) and Big Data departments. ETL (Extract, Transform, Load) processes, Data Lakes architecture, and the mastery of software like Power BI and Tableau have become the backbone of top-tier US startups and unicorns.

The Harvard Business Review has repeatedly highlighted that the professional who can translate complex data into business language is a modern corporation's most valuable asset. It's not enough to have the data; you must know how to tell a story with it (Data Storytelling).

The Job Market: The Hunt for Data Talent

With this paradigm shift, the demand for Data Engineers, BI Analysts, Data Scientists, and Analytics Engineers has skyrocketed. International companies—especially in the US and Europe—are aggressively hiring global professionals for 100% US Remote roles, offering highly competitive six-figure compensation packages.

For these companies, which use rigorous Applicant Tracking Systems (ATS like Ashby, Workday, and Greenhouse), the ideal candidate is one who seamlessly blends technical mastery (SQL, Python, DAX) with a sharp business acumen.


References and Recommended Reading

  • McKinsey & Company: The data-driven enterprise of 2025.
  • Harvard Business Review: How to Build a Data-Driven Culture.
  • Gartner: Top Trends in Data and Analytics.

Master the art of turning data into revenue?

The best US startups and global tech companies are actively looking for analytical professionals like you, offering remote roles with premium compensation. Don't miss out on the top Data, BI, and Machine Learning opportunities in the market.