At a Glance
- Tasks: Design, build, and deploy AI systems that deliver real business outcomes.
- Company: Join OpenAI, a leader in AI research and deployment.
- Benefits: Hybrid work model, relocation assistance, and a supportive team culture.
- Other info: Collaborate with top enterprises and influence product evolution.
- Why this job: Make a meaningful impact on the future of AI technology.
- Qualifications: Experience in AI/ML systems and strong coding skills, especially in Python.
The predicted salary is between 72000 - 88000 £ per year.
OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere.
As an Applied AI Engineer you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands‑on engineering, and customer leadership to take ambitious ideas from use‑case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real‑world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in London. 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 enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria.
- Design, build, and deploy AI systems that solve important customer problems and produce measurable business outcomes.
- Work hands‑on in code to build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators.
- Make sound technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance.
- Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive blockers toward resolution.
- Help customers progress from promising prototypes to reliable production systems, sustained adoption, and scaled impact.
- Partner closely with customer engineering teams and OpenAI Product, Research, Engineering, Security, and go‑to‑market teams, translating deployment experience into high‑signal product feedback.
- Create reusable architectures, tooling, playbooks, and technical guidance that accelerate future enterprise deployments.
You’ll thrive in this role if you:
- Have a demonstrated track record of designing, building, and delivering AI or machine‑learning 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, customer engineering, solutions architecture, or technical consulting.
- Can point to substantial personal contributions in code, architecture, evaluation, debugging, or production engineering—not only program or stakeholder management.
- Are highly proficient in Python and comfortable working across an AI application stack; experience with JavaScript, TypeScript, or another relevant language is valuable.
- Understand how to evaluate AI systems systematically using representative data, graders, production signals, and human judgment.
- Have navigated enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance, and cost.
- Can connect technical decisions to customer workflows, adoption, and measurable business outcomes.
- Communicate with clarity and credibility across hands‑on engineers, technical leaders, security teams, product leaders, and executives.
- Bring high agency, strong technical judgment, and end‑to‑end ownership in ambiguous environments.
- Learn quickly, challenge assumptions constructively, and collaborate with humility; experience in a particular industry or with OpenAI products is not required.
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.
Applied AI Engineer employer: OpenAI
OpenAI is an exceptional employer, offering a dynamic work environment in London where innovation thrives. With a strong emphasis on employee growth, you will have access to cutting-edge technology and collaborative projects that foster professional development. The company's commitment to reliability and optimization in machine learning ensures that your contributions will have a meaningful impact in the field.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI Engineer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at OpenAI or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to OpenAI.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like OpenAI.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like OpenAI that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Applied AI Engineer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at OpenAI.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at OpenAI and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at OpenAI
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If OpenAI uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.