Director, Forward-Deployed Engineering
I
InnovaccerHealthcare technology
United StatesFull-TimeDirector
Salary not disclosed
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Job Details
- Experience
- 12+ years in software engineering, technical consulting, or enterprise systems architecture; 5+ years within US Healthcare, HealthTech, or Digital Health; 5+ years managing a manager-of-managers organization or multiple concurrent, customer-facing technical delivery teams.
- Required Skills
- Data engineering
Requirements
- Have 12+ years of experience in software engineering, technical consulting, or enterprise systems architecture.
- Bring 5+ years of experience in US Healthcare, HealthTech, or Digital Health, working directly with clinical data ecosystems.
- Have 5+ years managing a manager-of-managers organization or multiple concurrent, customer-facing technical delivery teams.
- Hold a bachelor’s degree in Computer Science, Biomedical Engineering, or Health Informatics, or have equivalent practical experience.
- Have hands-on experience building, optimizing, and deploying enterprise-grade AI agents.
- Be proficient in designing and managing batch and real-time big data processing systems.
- Have experience with pipeline orchestration, Medallion Architecture, and end-to-end ETL/ELT pipeline engineering.
- Have operational knowledge of healthcare standards including HL7, FHIR, C-CDA, and X12/EDI.
Responsibilities
- Hire, mentor, and scale customer-facing engineering teams across regions, allocating resources across health systems, payers, and life sciences clients.
- Oversee implementation delivery plans from discovery through live production.
- Align engineering execution with customer business and clinical metrics, including administrative burden and workflow efficiency.
- Establish organizational standards for data integrity, product quality, architectural reviews, and customer sign-off.
- Guide teams building pipelines for structured and unstructured healthcare data using HL7, FHIR, and DICOM.
- Standardize validation frameworks to sanitize, deduplicate, and normalize healthcare data for AI/ML use.
- Implement automated data-quality testing and schema enforcement before ingestion.
- Oversee enterprise platform configuration and integration with production EHR systems and provider workflows.
- Design pre-sales and post-sales technical solution architectures aligned with customer requirements and platform capabilities.
- Oversee development, integration, optimization, and fine-tuning of AI agents, and enforce deployment guardrails and real-time monitoring.
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