前线部署工程师（FDE），医疗健康 - 旧金山
Forward Deployed Engineer (FDE), Healthcare - SF
关于团队
OpenAI 的前向部署工程团队与医疗保健组织合作，将生产级 AI 系统部署到临床、运营和面向客户的工作流程中。我们工作在客户部署与核心平台开发的交界处，通过客户合作定义可重复的架构、评估、集成和运营标准，以应对复杂且受监管的医疗环境。
关于职位
我们正在招聘一名前向部署工程师（FDE），负责在医疗保健组织（包括保险公司、提供者、医疗系统和医疗技术公司）内部署我们的模型。您将负责从头到尾的部署工作，包括技术调研、架构设计、实施、评估、生产化以及交接，将复杂的客户工作流程、数据、基础设施和法规限制转化为生产级 AI 系统。
您将通过生产采用率、可衡量的工作流程影响以及建立客户特定基准、验收标准和上线准备度的评估循环来衡量成功。您将直接与客户的工程技术及运营团队合作，并与内部的业务、研究、产品、工程和安全团队协作，交付解决方案并将部署经验转化为产品改进。该职位负责技术方案；不需负责商业或高管关系。
该职位位于旧金山。我们采用每周 3 天在办公室的混合办公模式。我们提供搬迁协助。需要最多 50% 的出差。
在此职位中，您将：
- 从客户调研和工作流程范围确定，到架构设计、亲自实施、评估、生产部署、采用和交接，全程负责技术方案。
- 与客户工程师、操作人员和领域专家可信地合作，解决模糊的问题，定义范围，并将保险、提供者或医疗系统的工作流程转化为技术需求和可衡量的结果。
- 设计和实现与客户基础设施、企业 API、数据平台、电子健康记录、理赔系统和操作工具集成的生产级 AI 应用和代理系统。
- 在处理受保护的健康信息（PHI）、HIPAA、隐私、安全、授权、治理、可审计性及其他受监管交付要求时，建立适当的保障措施。
- 定义并实施评估、验证证据，
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About the Team
OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments.
About the Role
We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems.
You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required.
This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.
In this role, you will:
- Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff.
- Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and measurable outcomes.
- Design and implement production AI applications and agentic systems that integrate with customer infrastructure, enterprise APIs, data platforms, electronic health records, claims systems, and operational tools.
- Build with appropriate safeguards for protected health information (PHI), HIPAA, privacy, security, authorization, governance, auditability, and other regulated-delivery requirements.
- Define and operationalize evaluations, validation evidence, human-review workflows, escalation paths, and launch criteria that measure model and system quality against customer-specific acceptance thresholds.
- Use evaluation results, error analysis, observability, and customer feedback to improve system reliability, performance, model selection, workflow impact, and production readiness.
- Distill deployment learnings into reference architectures, interoperability and integration patterns, evaluation harnesses, security controls, and reusable technical primitives for healthcare and other regulated enterprise environments.
You might thrive in this role if you:
- Bring 6+ years of software engineering, ML/AI engineering, solutions engineering, technical consulting, or comparable experience, with the technical depth
- Have operated as a senior engineer, tech lead, or deployment owner who is trusted to make technical decisions in ambiguous environments.
- Are deeply hands-on and have personally owned technical discovery, architecture, implementation, evaluation, productionization, and handoff for complex customer-facing or enterprise systems.
- Have healthcare experience including payer workflows, provider operations, EHR systems, or interoperability standards such as Epic, HL7, and FHIR.
- Have exposure to provider or health-system workflows such as clinical operations, revenue cycle management, patient access, or contact centers; or to EHR and interoperability technologies such as Epic, Oracle Health/Cerner, MEDITECH, HL7, FHIR, or health information exchanges.
- Have shipped complex systems as a forward deployed or customer engineer, an engineer inside a payer, provider, or health system, a builder at an EHR, interoperability, revenue cycle, payer-tech, or healthcare infrastructure company, a hands-on technical consultant or integrator, a solutions architect for regulated enterprises, or a technical founder or early engineering leader.
- Apply strong judgment to AI evaluation, privacy, security, governance, and reliability. Prior FDE titles, clinical credentials, and experience across every healthcare domain are not required.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf.
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