Applied AI Engineer, Digital Natives

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 Munich. 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 and digital native 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 might 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, product engineering or technical consulting.
• Are fluent in both German and English
• Can point to substantial personal contributions in code, architecture, evaluation, debugging, or engineering of production systems—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.

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 https://cdn.openai.com/policies/eeo-policy-statement.pdf.

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 https://form.asana.com/?d=57&k=5MqR40fZd7jlxVUh5J-UeA. 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 https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57.

OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf

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.

Wir zeigen einen Auszug und einen Link je Anzeige, und den vollen Text, wenn die Quelle es erlaubt. Genannte Marken und Logos gehören ihren Inhabern.

Quelle: Statistisches Bundesamt (Destatis), Tabelle; dl-de/by-2-0; eigene Berechnung

Veröffentlicht am 01. Nov. 2026

Veröffentlicht am 01. Nov. 2026