Applied AI Engineer, Enterprise - Healthcare Life Sciences (HLS)
About The Position
The Enterprise Applied AI Engineer serves as a technical partner to leading organizations in the Healthcare and Life Sciences segment, helping turn ambitious AI use cases into durable production systems and adoption at scale. The role combines deep technical judgment with hands-on engineering leadership on complex customer deployments, including writing and debugging code, building evaluation systems, resolving integrations, and advising on model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. The engineer works across clinical, operational, administrative, and research workflows, translating security, privacy, and governance requirements into practical deployment decisions. Success is measured by durable production systems, sustained adoption, and meaningful business impact. Deployment experience also informs the evolution of OpenAI products. The role can be based 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
- Proficiency in Python and ability to work across model APIs, agent and tool development, retrieval and data pipelines, evaluation, observability, integrations, and production operations.
- Experience systematically evaluating AI systems 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.
- Ability to communicate clearly and credibly with hands-on engineers, technical leaders, security and product teams, and executives.
- End-to-end ownership, strong technical judgment, and effectiveness in ambiguous situations.
- Ability to learn quickly, challenge assumptions constructively, and collaborate with humility.
Nice To Haves
- Experience designing, building, and shipping AI or machine-learning systems in enterprise environments, taking them from prototype to production, with substantial contributions in coding, architecture, evaluation, debugging, or production engineering.
- Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, customer engineering, solutions architecture, or technical consulting.
- Experience with JavaScript, TypeScript, or another relevant language.
- Experience delivering AI or software in healthcare, life sciences, or similarly complex regulated enterprises, with measurable outcomes beyond a proof of concept and familiarity with sensitive data, legacy systems, and interoperability.
- Healthcare or life sciences experience is strongly preferred; strong candidates from other regulated enterprise environments are also encouraged to apply.
- Prior OpenAI product experience is not required.
Responsibilities
- Design, build, evaluate, and deploy AI systems hands-on in code, taking them from prototype to reliable production and scaled adoption to solve customer problems and deliver measurable 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 drive blockers to resolution.
- Partner with customers’ engineering teams and OpenAI Product, Research, Engineering, Security, and Go-to-Market teams, turning deployment experience into actionable product feedback.
- Work with customer security, privacy, clinical, and business teams to design responsible AI deployments, including data handling, access controls, evaluation, human oversight, and monitoring.
- Create reusable architectures, tooling, playbooks, and technical guidance to accelerate future enterprise deployments.
Benefits
- Relocation assistance to new employees
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
