OpenAI의 엔터프라이즈 AI 배포 엔지니어는 고객의 비즈니스 문제를 해결하기 위해 AI 시스템을 설계하고 프로덕션 환경에 배포하는 역할을 수행합니다. Python을 활용한 실무 엔지니어링 능력과 AI 시스템 아키텍처 설계 경험이 필수입니다. 고객과 긴밀히 협력하여 프로토타입부터 실제 운영까지 전 과정을 주도하며, 기술적 판단력을 바탕으로 확장 가능한 솔루션을 구축합니다.
OpenAI’s AI Deployment 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 Enterprise AI Deployment 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.
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.
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.
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.
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