EU remote
Director Forward-Deployed Engineering
About this role
About the Role As the Director of Engineering, FDE and Customer Outcomes, you will lead an elite organization of multiple cross-functional engineering teams, each dedicated to a portfolio of tier-one healthcare customers. You are ultimately accountable for the technical delivery, enterprise configuration, and operational success of our AI-driven platform within complex healthcare ecosystems. Each team under your leadership operates with high autonomy, directly owning their customer delivery plans, data quality standards, and clinical/business outcomes.
You will mentor engineering managers and technical leads across a global footprint to architect robust data ingestion pipelines, configure complex enterprise software, and deploy production-grade, compliant AI agents into live healthcare environments. A Day in the Life Global Team Leadership & Delivery Ownership Scale and Govern Multiple Teams: Hire, mentor, and scale multiple customer-facing engineering teams across regions, optimizing global resource allocation across health systems, payers, and life sciences clients.
Delivery Plan Accountability: Empower autonomous teams to own, track, and execute comprehensive implementation delivery plans, navigating critical paths from discovery to live production. Customer Outcome Management: Focus engineering execution on direct business and clinical metrics (reducing administrative burden, improving workflow efficiency) to drive customer retention and high NPS/CSAT. Quality Assurance & Standards: Establish baseline organizational standards for data integrity, product quality, architectural reviews, and formal customer sign-off criteria.
Data Ingestion & Data Quality Clinical Data Ingestion: Guide teams in building high-throughput pipelines to ingest structured and unstructured datasets (EHR notes, lab results, imaging metadata, claims) via HL7, FHIR, and DICOM. Data Quality & Normalization: Standardize validation frameworks to sanitize, deduplicate, and normalize raw, heterogeneous healthcare data for downstream AI/ML consumption. Deterministic Guardrails: Implement automated data-quality testing and schema enforcement protocols to intercept data corruption or format mismatches pre-ingestion, ensuring absolute clinical data integrity.