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Lead AI Infrastructure Engineering Manager
PresencialTiempo completoAI EngineeringMedical Devices
Lead a team of data and software engineers developing data platforms, AI integration infrastructure, verification systems, and scalable deployment capabilities for healthcare products.
Responsabilidades
- Lead, mentor, and develop data and software engineering teams.
- Set team priorities, roadmaps, technical standards, and execution plans.
- Design and maintain enterprise data infrastructure, repositories, and scalable data management solutions.
- Own clinical data collection, anonymization, curation, annotation, versioning, traceability, and lifecycle management.
- Develop integrations with internal systems and data sources while ensuring secure, compliant data access.
- Build reusable AI integration frameworks, SDKs, plugins, APIs, services, and compatibility layers.
- Enable AI deployment across Linux- and Windows-based medical device platforms.
- Develop tools and environments for algorithm execution, debugging, evaluation, reproducibility, and portability.
- Establish automated unit, integration, regression, performance, and system testing frameworks.
- Lead CI/CD and release infrastructure for the AI software lifecycle.
- Support algorithm verification, system validation, regulatory submissions, audits, and traceability.
- Drive compliance with medical-device quality systems, FDA requirements, design controls, and software lifecycle processes.
- Collaborate with Algorithm, Clinical, Product, Verification, Regulatory, and Systems Engineering teams.
Requisitos
- Bachelor’s or master’s degree in computer science, software engineering, data engineering, or a related technical field.
- At least 5 years of experience in software, data, platform engineering, or a related discipline.
- At least 2 years of experience leading technical teams.
- Experience designing and operating data management platforms and workflows.
- Strong software architecture and systems integration experience.
- Experience building APIs, SDKs, services, and distributed systems.
- Strong Python programming skills and modern software development expertise.
- Advanced knowledge of SQL, databases, and large-scale data processing.
- Experience with automated testing frameworks and CI/CD pipelines.
- Strong leadership, communication, and stakeholder management skills.
Se valora
- Experience in medical devices, healthcare software, or other regulated industries.
- Experience with AI/ML development workflows, MLOps, and production model integration.
- Knowledge of DICOM, FHIR, or other healthcare and medical imaging standards.
- Experience with Linux and Windows development environments.
- Experience with cloud platforms and modern DevOps technologies.
- Familiarity with FDA design controls, software lifecycle processes, and medical-device regulatory requirements.