Engineering Manager, AI Data Platform

🔥 vor 28 Minuten

🗽 New York – Remote

infoinfo

💵 $200.000 - $250.000 / Jahr

⏰ Vollzeit

🟠 Senior

🔴 Experte

👮‍♀️ Leiter Softwareentwicklung

🗣️🇺🇸🇬🇧 Englisch erforderlich

Woher diese Stelle stammt

Veröffentlicht auf der Karriereseite von Imagen Technologies, nicht über eine Jobbörse

Von Remote Rocketship zum ersten Mal gesehen vor 28 Minuten

Logo of Imagen Technologies

Imagen Technologies

51 - 200 Mitarbeiter

🏥 Gesundheitswesen

🤖 Künstliche Intelligenz

Healthcare • Artificial Intelligence

Imagen bietet vor Ort technologiegestützte Diagnoselösungen, die es Allgemeinpraxen ermöglichen, klinische Ergebnisse, Patientenzufriedenheit und finanzielle Ergebnisse zu maximieren.

Beschreibung

• Hire and manage a team of data engineers ranging from staff to mid-level • Establish team processes, engineering culture, and development practices • Coach and grow engineers across multiple levels • Take full technical and operational ownership of the AI Data Platform • Ingest, de-identify, transform, and serve clinical imaging data such as DICOM and reports • Ensure the platform is reliable, scalable, and secure • Set the technical direction and execute the platform roadmap • Prioritize scalability improvements, new capabilities, and technical debt reduction in alignment with business OKRs • Implement data quality frameworks, validation checks, and governance processes • Ensure compliance with HIPAA and other applicable regulations • Serve as the primary point of contact for AI, Product, Clinical, and Regulatory teams • Translate stakeholder needs into a prioritized roadmap and ensure reliable delivery • Report to the Head of Engineering and partner with the Chief AI Officer, Product leaders, Clinical team, and engineers across the organization

🎯 Anforderungen

• Mission-driven and passionate about building foundational technology to improve healthcare • 8+ years of experience in software or data engineering • At least 2 years in an engineering management role • Proven track record of building engineering teams or scaling teams through a significant growth phase • Strong technical foundation in data engineering • Comfortable reviewing system designs, making architectural decisions, and contributing code in Python and SQL when needed • Experience with cloud-native data platforms and modern data infrastructure, including data lakes, data warehouses, ETL/ELT pipelines, and workflow orchestration tools like Airflow, Prefect, or Dagster • Demonstrated ability to manage cross-functional stakeholders and translate business needs into engineering priorities • Experience operating in a fast-paced, high-growth environment where priorities shift and ambiguity is the norm • BS in Computer Science or a related field, or equivalent real-world experience • Experience in healthcare, healthtech, or another regulated industry preferred • Experience with MLOps or building infrastructure that supports machine learning workflows preferred • Experience with multi-cloud environments and cloud cost optimization preferred

🏖️ Vorteile

• Equity • Benefits • Remote work

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