Forward Deployed Engineer (FDE), Healthcare - SF
Forward Deployed Engineer · Senior · Full Time
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Role
What you'll do.
OpenAI seeks a Forward Deployed Engineer (FDE) to lead end-to-end deployments of production AI systems within healthcare organizations, including payers, providers, and health systems. In this role, you'll translate complex clinical workflows, data infrastructure, and regulatory constraints into scalable AI solutions while collaborating with customer technical teams and internal cross-functional partners. This position requires 6+ years of software engineering or ML/AI deployment experience, healthcare domain knowledge, and a track record of shipping complex enterprise systems in regulated environments.
Responsibilities
- End-to-End Technical Ownership: Own the complete deployment lifecycle from customer discovery and workflow scoping through architecture design, hands-on implementation, evaluation, production deployment, adoption tracking, and knowledge handoff. Lead technical discovery sessions to understand customer pain points, operational workflows, and success metrics.
- Healthcare Workflow Translation: Partner credibly with customer engineers, operators, and domain experts to frame ambiguous healthcare problems, define technical scope, and translate payer, provider, or health system workflows into concrete technical requirements and measurable business outcomes.
- Production AI System Architecture and Implementation: Design and implement production-grade AI applications and agentic systems that integrate seamlessly with customer infrastructure, enterprise APIs, data platforms, electronic health records (EHR), claims systems, and operational tools while maintaining enterprise-grade reliability and performance.
- Regulatory Compliance and Data Governance: Build systems with comprehensive safeguards for protected health information (PHI), ensure HIPAA compliance, implement privacy and security controls, establish authorization frameworks, maintain governance standards, and establish auditability requirements for regulated healthcare delivery.
- Evaluation and Quality Assurance: Define and operationalize comprehensive evaluations, validation evidence, human-review workflows, escalation paths, and launch criteria that measure model and system quality against customer-specific acceptance thresholds and measurable clinical or operational impact.
- Continuous Improvement and Observability: Use evaluation results, error analysis, production observability, and customer feedback to iteratively improve system reliability, performance, model selection, workflow impact, and overall production readiness throughout the deployment lifecycle.
- Knowledge Distillation and Standardization: Distill deployment learnings and best practices into reusable reference architectures, interoperability patterns, integration standards, security controls, evaluation frameworks, and technical primitives that benefit future healthcare and regulated enterprise deployments across OpenAI.
- Cross-Functional Collaboration: Collaborate directly with customer technical and operational teams alongside internal Business, Research, Product, Engineering, and Security partners to deliver solutions, identify product gaps, and translate deployment insights into product improvements for the broader platform.
Qualifications
What we look for.
Technical
Production System Design and Architecture
Expert-level experience designing, architecting, and implementing production-grade systems with emphasis on reliability, scalability, observability, and operational excellence.
AI/ML System Evaluation and Validation
Deep expertise in developing evaluation frameworks, validation strategies, and quality assessment methodologies for AI systems, including model selection, performance benchmarking, and production readiness criteria.
Healthcare Data Integration
Strong proficiency with healthcare data standards and integration technologies including Electronic Health Records (EHR) systems, interoperability protocols (HL7, FHIR), health information exchanges, claims systems, and enterprise data platforms.
Security, Privacy, and Compliance
Solid understanding of healthcare compliance frameworks (HIPAA, security controls), protected health information (PHI) handling, privacy engineering, authorization frameworks, audit requirements, and governance standards for regulated environments.
Full-Stack Application Development
Hands-on capability across the full application stack including backend systems, APIs, data pipelines, database design, frontend integration, and deployment infrastructure.
Enterprise API Integration
Experience integrating with complex enterprise APIs, third-party systems, legacy infrastructure, and diverse technology stacks common in healthcare organizations.
Education
Bachelor's Degree in Computer Science or Related Field
Preferred degree in Computer Science, Software Engineering, Electrical Engineering, Mathematics, or equivalent field with strong technical foundation. Advanced degrees not required but relevant.
Experience
6+ Years Software Engineering or AI/ML Experience
Minimum 6+ years of professional experience in software engineering, ML/AI engineering, solutions engineering, technical consulting, or equivalent roles with demonstrated technical depth and breadth.
Senior-Level Technical Decision Making
Proven track record operating as a senior engineer, tech lead, or deployment owner trusted to make independent technical decisions in ambiguous, complex environments with limited guidance.
Complex System Ownership
Hands-on experience personally owning technical discovery, architecture, implementation, evaluation, productionization, and handoff for complex customer-facing or enterprise systems at scale.
Healthcare Ecosystem Experience
Demonstrated experience with healthcare workflows including payer operations, provider workflows, EHR systems, or interoperability standards. Background may include work as a forward deployed engineer, customer engineer within healthcare organizations, healthcare infrastructure builder, or solutions architect for regulated enterprises.
Enterprise Systems Deployment
Shipped complex systems as a forward deployed engineer, engineer inside a payer/provider/health system, builder at an EHR company, interoperability platform engineer, revenue cycle technology specialist, healthcare infrastructure company developer, or hands-on technical consultant/integrator.
Skills
Required
Python
Expert-level proficiency in Python for AI/ML system development, data processing, and production backend services.
AI/ML Frameworks and Model Deployment
Hands-on experience with modern AI frameworks, LLM integration patterns, prompt engineering, model fine-tuning, and deploying AI systems to production environments.
API Design and Development
Strong expertise designing and implementing RESTful or gRPC APIs, handling enterprise integrations, error handling, and scalable service architectures.
Database Systems
Proficiency with both relational (PostgreSQL, MySQL) and NoSQL databases, with experience in data modeling, query optimization, and handling large-scale healthcare datasets.
Healthcare Data Standards
Working knowledge of healthcare interoperability standards including HL7, FHIR, and experience with Electronic Health Record (EHR) systems integration.
System Design and Architecture
Ability to design scalable, maintainable, and reliable system architectures suitable for enterprise and regulated healthcare environments.
Problem Solving and Requirements Translation
Exceptional ability to translate ambiguous customer requirements, complex workflows, and regulatory constraints into clear technical specifications and implementation plans.
Customer Collaboration and Communication
Strong communication skills for working effectively with non-technical stakeholders, healthcare domain experts, and cross-functional teams to gather requirements and explain technical decisions.
Preferred
TypeScript/JavaScript
Nice to haveExperience with TypeScript or JavaScript for full-stack development, particularly for customer-facing applications or real-time systems.
Cloud Infrastructure (AWS/Azure/GCP)
Nice to haveHands-on experience deploying and managing systems on cloud platforms, including containerization, orchestration, and infrastructure-as-code practices.
Docker and Kubernetes
Nice to haveProficiency containerizing applications and orchestrating deployments at scale, important for enterprise healthcare deployments.
LLM Platforms and Agentic Systems
Nice to havePractical experience building with Large Language Models, implementing AI agents, prompt engineering, and deploying generative AI applications.
Healthcare Workflow Experience
Nice to haveDirect experience with healthcare domains including clinical operations, revenue cycle management, patient access workflows, payer operations, or health system IT.
HIPAA and Healthcare Compliance
Nice to haveDemonstrated understanding of HIPAA requirements, healthcare data privacy regulations, and security compliance frameworks in healthcare settings.
Epic, Cerner, or HL7/FHIR Integration
Nice to haveHands-on experience integrating with specific EHR systems like Epic or Cerner, or building with HL7 and FHIR standards for healthcare interoperability.
Observability and Monitoring
Nice to haveExperience implementing comprehensive observability solutions, logging, metrics, tracing, and alerting for production systems.
Technical Consulting or Solutions Architecture
Nice to haveBackground in customer-facing technical roles such as solutions architecture, technical consulting, or pre-sales engineering for enterprise products.
Agentic AI Systems
Nice to haveExperience designing and implementing agentic systems, autonomous workflows, and AI systems that operate with minimal human intervention.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 198,000 – 294,000
Equity·Stock options
Benefits
Relocation Assistance
OpenAI provides relocation support for qualified candidates relocating to San Francisco.
Hybrid Work Model
Flexible work arrangement with 3 days in-office per week requirement, allowing for remote work flexibility.
Comprehensive Health Coverage
Competitive health insurance benefits including medical, dental, and vision coverage.
Retirement Benefits
401(k) retirement savings plan with company matching contributions.
Professional Development
Access to learning resources, conferences, and professional development opportunities in AI and healthcare technology.
Equity Participation
Stock options or equity participation in OpenAI's growth and success.
Full posting
Original listing.
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.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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