OpenAI11 дней назад
AI Deployment Engineer, Enterprise
Зарплата не указана
Полная занятостьУдалёнка
Обязанности
- 01Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria
- 02Design, build, and deploy AI systems that solve important customer problems and produce measurable business outcomes
- 03Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators
- 04Make sound technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance
- 05Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive blockers toward resolution
- 06Help customers progress from promising prototypes to reliable production systems, sustained adoption, and scaled impact
- 07Partner closely with customer engineering teams and OpenAI Product, Research, Engineering, Security, and go-to-market teams, translating deployment experience into high-signal product feedback
- 08Create reusable architectures, tooling, playbooks, and technical guidance that accelerate future enterprise deployments
Требования
- 01Have a demonstrated track record of designing, building, and delivering AI or machine-learning systems in enterprise environments, including taking systems from prototype to production
- 02Can point to substantial personal contributions in code, architecture, evaluation, debugging, or production engineering—not only program or stakeholder management
- 03Are highly proficient in Python and comfortable working across an AI application stack
- 04Understand how to evaluate AI systems systematically using representative data, graders, production signals, and human judgment
- 05Have navigated enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance, and cost
- 06Can connect technical decisions to customer workflows, adoption, and measurable business outcomes
- 07Communicate with clarity and credibility across hands-on engineers, technical leaders, security teams, product leaders, and executives
- 08Bring high agency, strong technical judgment, and end-to-end ownership in ambiguous environments
- 09Learn quickly, challenge assumptions constructively, and collaborate with humility