Healthcare AI Deployment Engineer - Hybrid NYC

Alfie; New York (NY); Híbrido; USD 185.000 - 300.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Relocation assistance

Hybrid work model

Travel 50%

Descripción de la vacante

OpenAI’s Forward Deployed Engineering team hires a Forward Deployed Engineer to own end-to-end deployments of models within healthcare, including payers, providers, and health systems. You will lead discovery, architecture, implementation, evaluation, and productionization.

This NYC-based role uses a hybrid model with three days in the office per week and relocation assistance. Travel up to 50% is required, and you will partner with customer engineers and internal teams to translate workflows

Formación

• 6+ years of software engineering, ML/AI engineering, solutions engineering, 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.

Responsabilidades

• 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 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.

Conocimientos

ML/AI engineering

Solutions engineering

Software engineering

Technical consulting

Descripción del empleo

OpenAI’s Forward Deployed Engineering team hires a Forward Deployed Engineer to own end-to-end deployments of models within healthcare, including payers, providers, and health systems. You will lead discovery, architecture, implementation, evaluation, and productionization.

This NYC-based role uses a hybrid model with three days in the office per week and relocation assistance. Travel up to 50% is required, and you will partner with customer engineers and internal teams to translate workflows