Description
Compensation
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The salary range for this position is $198K – $294K, with generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
Benefits include:
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend to fuel your professional growth
- Daily meals in our offices, and meal delivery credits as eligible
- Relocation support for eligible employees
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
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.
Responsibilities
- 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.
Requirements
- 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.