Data & AI Platform Team Leader

Job Description Summary

e are looking for a Data & AI Infrastructure Team Leader to lead a team of Data Engineers and Software Engineers developing innovative clinical applications that power next-generation AI healthcare solutions. The team provides data management solutions, AI development infrastructure, software integration frameworks, evaluation and verification capabilities, and scalable deployment mechanisms.

This role requires end-to-end ownership and a broad systems perspective, from understanding customer needs and product requirements to enabling successful product delivery.

If you're looking for a meaningful opportunity to make a real impact on healthcare and help improve patients' lives, we'd love to hear from you.

Job Description

Key Responsibilities

Team Leadership

• Lead, mentor, and grow a team of Data Engineers and Software Engineers.
• Define team priorities, roadmap, and execution plans aligned with business and product objectives.
• Foster engineering excellence, accountability, collaboration, and continuous improvement.
• Drive effective cross-functional collaboration with Algorithm, Clinical, Product, Verification, Regulatory, and Systems Engineering teams.
• Establish technical standards, best practices, and development processes.
  
  

• Lead the design, development, and maintenance of enterprise-grade data infrastructure supporting AI development.
• Own database architecture, data repositories, and scalable data management solutions.
• Drive solutions for clinical data collection, anonymization, curation, annotation, versioning, traceability, and lifecycle management.
• Develop and maintain integrations with internal GE HealthCare systems and data sources.
• Ensure secure, compliant, and efficient data access mechanisms for global development teams.
• Support regulatory submissions through reproducible and auditable data preparation processes.
• Establish data governance standards, quality controls, and operational excellence practices.
  
  

• Lead development of software frameworks enabling integration of AI technologies into multiple product platforms and operating environments.
• Drive creation of reusable SDKs, plugins, APIs, and services that accelerate AI deployment across products.
• Support integration of AI solutions into Linux and Windows-based medical device platforms.
• Define and maintain AI integration architecture, deployment mechanisms, and compatibility layers.
• Enable rapid prototyping and evaluation environments for algorithm development teams.
• Drive development of tools supporting algorithm execution, debugging, performance evaluation, reproducibility, and portability across host systems.
  
  

• Establish automated testing frameworks covering unit, integration, regression, performance, and system-level testing.
• Lead development of CI/CD pipelines and release infrastructure supporting the AI software lifecycle.
• Ensure traceability, reproducibility, maintainability, and quality throughout the development process.
• Develop infrastructure supporting algorithm verification, system validation, and integration testing activities.
• Drive engineering best practices for software quality, reliability, scalability, and maintainability.
  
  

• Ensure all development activities comply with medical device quality systems and regulatory requirements.
• Support processes aligned with FDA regulations, design controls, software lifecycle requirements, verification, validation, and traceability.
• Establish infrastructure and workflows that enable compliant and efficient AI feature releases.
• Partner with Regulatory, Quality, and Product teams to support audits, submissions, and lifecycle management activities.
  
  

• B.Sc. or M.Sc. in Computer Science, Software Engineering, Data Engineering, or a related technical field.
• 5+ years of experience in software engineering, data engineering, platform engineering, or related disciplines.
• 2+ years of experience leading technical teams.
• Strong experience designing and operating data management platforms and workflows.
• Strong software architecture and system integration background.
• Experience building and maintaining APIs, SDKs, services, and distributed systems.
• Strong programming skills in Python and modern software development practices.
• Deep knowledge of SQL, databases, and large-scale data processing.
• Experience with automated testing frameworks and CI/CD pipelines.
• Excellent leadership, communication, and stakeholder management skills.
  
  

• Experience in medical devices, healthcare software, or other regulated industries.
• Experience supporting AI/ML development workflows and MLOps practices.
• Experience integrating AI models into production products.
• Knowledge of healthcare and medical imaging standards such as DICOM and FHIR.
• Experience with Linux and Windows development environments.
• Experience with cloud platforms and modern DevOps technologies.
• Familiarity with FDA design controls, software lifecycle processes, and regulatory requirements for medical devices.