OpenAI19 дней назад

Applied AI Engineer

Зарплата не указана

РЫНОК

16 333 ₽медиана по профессии

Data Scientist · 213 вакансий с указанной зарплатой

5 000половина предложений: 13 167–22 000123 000

Работодатель не указал зарплату — сравните с рынком сами.

Полная занятостьУдалёнка

Обязанности

01Partner 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.
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.

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. Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, customer engineering, solutions architecture, or technical consulting.
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; experience with JavaScript, TypeScript, or another relevant language is valuable.
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; experience in a particular industry or with OpenAI products is not required.