Forward Deployed Engineer (FDE), Healthcare

About the role

This role is centered on deploying production AI systems within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will own end-to-end deployments of our models, operating at the intersection of customer deployment and core platform development. The position requires leading technical discovery, architecture, implementation, evaluation, productionization, and handoff of complex, regulated healthcare environments. You will translate intricate customer workflows, data constraints, and regulatory requirements into robust, production-ready AI systems. Success is measured through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks and launch readiness. You will 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, while ownership of the commercial or executive relationship is not required.

Key facts

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.
• 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.
• Engage directly with healthcare-specific deployment constraints, including data residency, access controls, audit trails, and compliance documentation required for production environments.
• Conduct hands-on prototyping, proof-of-concept development, and iterative refinement based on customer feedback and operational performance metrics.
• Collaborate with internal teams to codify deployment patterns, operational playbooks, and architectural standards that can be scaled across similar healthcare customers.
• Drive the creation of detailed technical artifacts, including integration guides, evaluation dashboards, and runbooks that support ongoing operations and customer success.
• Act as a technical liaison between research, product, and customer teams to ensure alignment between deployed solutions and evolving product capabilities.
• Apply rigorous testing and validation practices to ensure that deployed systems meet defined performance, safety, and reliability criteria in real-world healthcare settings.
• Support the identification and resolution of production issues, working alongside platform and infrastructure teams to maintain high availability and security standards.
• Contribute to the development of tools and frameworks that simplify the deployment and monitoring of AI systems in regulated environments.

Requirements

• Bring 6+ years of software engineering, ML/AI engineering, solutions engineering, technical consulting, or comparable experience, with the technical depth to own complex technical solutions.
• 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.

Practical notes

This role is based in Seattle. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.