Senior DevOps Engineer building and scaling cloud infrastructure for Heidi's AI Care Partner platform. Collaborating with engineers and product teams to ensure reliability and automation in a hybrid work environment.
About the role
- DevOps Engineer responsible for cloud infrastructure and CI/CD for AI-driven clinical workflows at Cambio, a leading eHealth supplier.
Responsibilities
- Own, operate, and evolve our cloud infrastructure, primarily in Azure, with a roadmap toward Kubernetes / OpenShift.
- Build and maintain Kubernetes platforms, including Helm, ingress, RBAC, scheduling, and networking.
- Design and operate secure, automated CI/CD pipelines (Azure DevOps / GitHub Actions).
- Implement observability and monitoring using tools such as Prometheus, Grafana, Loki, or ELK.
- Apply DevSecOps principles across the stack, including identity, secrets management, network policies, and compliance.
- Deploy, monitor, and scale PostgreSQL / Supabase environments, including backup, performance, and reliability.
- Support and optimize GPU-based AI inference workloads, collaborating closely with backend and AI engineers.
- Act as a technical partner to the development teams, improving deployment, stability, and operational efficiency.
Requirements
- Several years of experience (typically 5+) working with DevOps, cloud engineering, or platform engineering in production environments.
- Strong experience with cloud infrastructure, ideally Azure (but experience from AWS or GCP is also valuable).
- Hands-on experience with containers and Kubernetes, or a clear ambition to move deeper into Kubernetes/OpenShift.
- Experience designing and maintaining CI/CD pipelines and infrastructure automation.
- Solid understanding of security principles across cloud, network, and application layers.
- Experience with monitoring, observability, and operating systems in production.
- Ability to take ownership, communicate technical decisions, and work closely with development teams.
- Comfort using modern AI tools as part of your engineering workflow to improve efficiency and quality.
- Experience with GPU workloads and real-time AI inference in production.
- Experience with microservices architectures and distributed systems.
- Experience working in regulated environments, such as healthcare or financial services.
- Familiarity with FastAPI / Python applications and how application design impacts infrastructure and operations.
Benefits
- Health insurance
- Professional development opportunities
- Flexible working hours
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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