Applied AI Engineer, Enterprise - EDU

OpenAI•San Francisco, CA

2d•$251,000 - $278,000

About The Position

The Applied AI Engineer, Enterprise - EDU serves as a technical partner to universities and other educational institutions, helping them turn AI use cases into reliable production systems and drive adoption at scale. The role combines technical leadership with hands-on engineering on complex customer deployments, including coding, debugging, building evaluation systems, resolving integrations, and guiding decisions about model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by durable production systems, sustained adoption, and meaningful business impact. Deployment experience also informs the evolution of OpenAI products. The role may be based in an office in New York City or San Francisco, or performed remotely. Office-based employees follow a hybrid model with three days per week in the office. Relocation assistance is offered to new employees.

Requirements

Personally designed, built, and shipped AI or machine-learning systems in enterprise environments, taking them from prototype to production and making substantial contributions through coding, architecture, evaluation, debugging, or production engineering.
High proficiency in Python and ability to work end to end across model APIs, agent and tool development, retrieval and data pipelines, evaluation, observability, integrations, and production operations.
Ability to evaluate AI systems systematically using representative data, automated graders, production signals, and human judgment.
Experience navigating enterprise production requirements, including integrations, reliability, observability, security, privacy, data governance, performance, and cost.
Ability to connect technical decisions to customer workflows, adoption, and measurable business outcomes.
Clear and credible communication with hands-on engineers, technical leaders, security and product teams, and executives.
End-to-end ownership, strong technical judgment, and ability to work effectively through ambiguity.
Ability to learn quickly, challenge assumptions constructively, and collaborate with humility.

Nice To Haves

Experience with JavaScript, TypeScript, or another relevant programming language.
Experience navigating education or research environments, including institutional data, privacy, access controls, and complex integrations.
Experience working with educational institutions, particularly universities, is preferred but not required.

Responsibilities

Design, build, evaluate, and deploy AI systems hands-on, from prototype through reliable production and scaled adoption, to solve customer problems and deliver measurable business outcomes.
Partner with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and success criteria.
Make technical decisions involving model selection, agent and tool design, retrieval, context design, data pipelines, evaluation, reliability, observability, latency, cost, safety, security, and governance.
Diagnose complex implementation challenges, reproduce failures, test hypotheses, and resolve blockers.
Partner with customer engineering teams and OpenAI Product, Research, Engineering, Security, and Go-to-Market teams to turn deployment experience into actionable product feedback.
Create reusable architectures, tooling, playbooks, and technical guidance to accelerate future enterprise deployments.