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Head of Engineering
| Company | Cardiosense |
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| Location | Chicago, IL, USA |
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| Salary | $153000 – $225000 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Expert or higher |
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Requirements
- Engineering management including hands-on operations experience within a full-stack medical device company including class II/III devices, mobile gateways, mobile/desktop apps, cloud infrastructure, and data science
- 10+ years SW development experience along with 5+ years of experience managing development teams through full product lifecycle: from concept, through commercialization, to production maintenance
- Strong experience with microservices/containerization (e.g. Docker, Kubernetes etc.), infrastructure automation tools (e.g. Terraform, CloudFormation, etc.), and public cloud service providers (e.g. GCP, Azure, AWS)
- Strong desire to lead and develop junior team members
Responsibilities
- Lead design, architecture, and development of software platform roadmaps
- Hire, coach, and groom a strong engineering organization optimized for lean, iterative, product development cycles
- Collaborate with product teams to translate user workflows into technical specifications and design implementations
- Develop and manage development budgets, resources, and timelines to ensure successful project delivery
- Directly manage the internal engineering team for development of software infrastructure. Oversee mechanical and electrical teams related to the development of wearable biosensor device
- Manage design and deployment of ML infrastructure from data ingestion to model deployment, supporting AI development from early feasibility to production rollout
- Define and implement agile software best practices, release management, CI/CD, code review, unit testing, and testing automation
- Ensure compliance with all relevant data privacy and cybersecurity standards
- Mentor and train team members on design techniques, systems architecture, and coding standards
Preferred Qualifications
- Experience working with IoT devices, health data, and digital signal processing
- Familiarity with model deep learning tools such as TensorFlow and PyTorch
- Working in regulated environments (e.g. FDA, ISO 270001, 13485, 62304, HIPAA, SOC2, etc.)
- Experience with HL7, Smart on FHIR and Mirth Interface Engine
