Cloud Infrastructure Architect for MedTech Innovations
3 dni temu
About Us
At illumicell AI, we're revolutionizing healthcare diagnostics by leveraging advanced AI and cutting-edge cell visualization technology. Our innovative approach spans Harvard's Pagliuca Life Lab and an R&D hub in Zurich, blending unconventional thinking with scientific rigor.
Your Mission
We're seeking a skilled Cloud Infrastructure Architect to design, build, and maintain our GCP infrastructure, supporting AI, high-volume data processing, and rapid growth. You'll collaborate with AI/ML experts, clinicians, and product teams to ensure our systems are robust, compliant, and ready to transform how fertility—and broader health—are understood.
Key Responsibilities
- Cloud Architecture and Deployment
- Lead the design of secure, scalable infrastructure (GCE, GKE, Cloud Run, etc.) tailored for MedTech environments.
- Establish architectural best practices and frameworks to optimize performance, security, and reliability.
- Containerization and Microservices
- Build containerized services using Docker and Kubernetes, promoting microservices patterns for efficient deployment and scaling.
- Use serverless (Cloud Functions) or managed platforms for faster iteration and reduced ops overhead.
- Data and AI/ML Integration
- Implement end-to-end data pipelines (Dataflow, Pub/Sub, BigQuery) and advanced analytics for large-scale clinical or research data.
- Collaborate with AI/ML teams on Vertex AI to manage data ingestion, model training, versioning, and cloud-based deployment.
- DevOps and CI/CD
- Define and maintain continuous integration and deployment pipelines (Cloud Build, GitHub Actions, or Jenkins).
- Drive infrastructure as code (Terraform or Deployment Manager) to automate provisioning and scaling.
- Security and Compliance
- Uphold stringent security protocols to meet regulatory standards (HIPAA, FDA guidance).
- Oversee access controls, encryption, logging, and monitoring to safeguard sensitive medical data.
- Collaboration and Mentorship
- Work closely with software engineers, data scientists, and clinicians to translate project goals into robust cloud solutions.
- Provide clear documentation and mentor junior engineers on cloud best practices.
Requirements
- GCP Experience
- Demonstrable work in designing and deploying production workloads on Google Cloud.
- Deep familiarity with GCP services for compute, storage, networking, security, and AI.
- Container and Serverless Expertise
- Proven track record with Docker, Kubernetes (GKE), and serverless frameworks (Cloud Functions/Run).
- Data Management and ML Pipelines
- Advanced skills in data ingestion, processing (e.g., Dataflow), and analytics (BigQuery).
- Bonus if you've integrated ML platforms like Vertex AI in real-world applications.
- DevOps and CI/CD Know-How
- Strong experience with automated builds, testing, and deployments (CI/CD).
- Infrastructure as code using Terraform or similar.
- MedTech or Healthcare Background (Nice-to-Have)
- Familiarity with regulatory compliance, HIPAA, and FDA guidelines.
- Understanding of healthcare data structures and integration challenges.
- Soft Skills
- Exceptional communication, both written and verbal.
- Collaborative mindset, comfortable working across cross-functional teams in a fast-paced startup.
Why Join Us?
- Transformative Impact
- We're redefining diagnostics by turning sperm into a digital biomarker for fertility and broader health insights—a chance to shape a new global standard.
- Vibrant Startup Culture
- Work with brilliant minds across Boston and Zurich, at the intersection of advanced AI, novel hardware, and ground-breaking medical research.
- Growth and Rewards
- Compensation starts on the lower side, but there's significant room for salary growth over time plus equity packages if you're the right fit.
- Have a direct hand in building a transformative product that merges AI, GCP, and cutting-edge healthcare tech.
- Innovation and Autonomy
- We move quickly and encourage creative solutions—no idea is off the table.
- Your expertise will drive key decisions in architecture, strategy, and implementation.
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