The opportunity
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…
What you'll do
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.
What they're looking for
- 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.
- 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.
