AI Deployment Engineer, Enterprise
$197,000–$278,000 year
RemoteNew York City, New York, United States or San Francisco, California, United States
Job Summary
Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, and evaluation strategies. Design, build, and deploy AI systems that solve important customer problems, producing measurable business outcomes through prototypes, production launches, and scaled impact. Work hands-on in code to build evaluation harnesses, reference implementations, and production accelerators while making 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 and sustained adoption. Create reusable architectures, tooling, playbooks, and technical guidance that accelerate future enterprise deployments. Collaborate closely with customer engineering teams and OpenAI Product, Research, Engineering, Security, and go-to-market teams to translate deployment experience into high-signal product feedback. This role is based in SF or NYC with a hybrid work model of 3 days in the office per week and offers relocation assistance.
Required Qualifications
- demonstrated track record of designing, building, and delivering AI or machine-learning systems in enterprise environments, including taking systems from prototype to production
- substantial personal contributions in code, architecture, evaluation, debugging, or production engineering
- highly proficient in Python
- comfortable working across an AI application stack
- experience with JavaScript, TypeScript, or another relevant language
- ability to evaluate AI systems systematically using representative data, graders, production signals, and human judgment
- experience navigating enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance, and cost
- ability to connect technical decisions to customer workflows, adoption, and measurable business outcomes
- ability to communicate with clarity and credibility across hands-on engineers, technical leaders, security teams, product leaders, and executives
- high agency, strong technical judgment, and end-to-end ownership in ambiguous environments
- ability to learn quickly, challenge assumptions constructively, and collaborate with humility
Desired Qualifications
- experience in a particular industry
- experience with OpenAI products
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