job description
Join Optum as a DevOps Engineer (AI/ML) and drive innovation in cloud infrastructure, automation, and AI-driven solutions. Based in beautiful Bali, you'll play a pivotal role in building secure, scalable platforms that enhance global health outcomes. Leverage cutting-edge technologies like Azure, Kubernetes, and CI/CD pipelines to optimize performance and reliability. This is a unique opportunity to blend technical expertise with impactful work in a dynamic, collaborative environment.
As part of our global team, you'll collaborate with AI/ML specialists, cloud architects, and healthcare technologists to deploy solutions that transform patient care. Enjoy the flexibility of remote work with the option to operate from Bali, a hub for digital nomads and tech innovators.
Responsibility
- Design, implement, and manage scalable cloud infrastructure on Azure with a focus on AI/ML workloads.
- Automate deployment, monitoring, and maintenance using CI/CD pipelines (e.g., Azure DevOps, GitHub Actions).
- Optimize system performance, security, and cost-efficiency through infrastructure-as-code (Terraform, ARM templates).
- Collaborate with AI/ML teams to deploy and scale models in production environments.
- Ensure high availability and disaster recovery for critical healthcare applications.
- Monitor and troubleshoot cloud environments using tools like Prometheus, Grafana, and Azure Monitor.
- Implement security best practices (e.g., IAM, encryption, compliance standards).
- Mentor junior engineers and contribute to DevOps best practices documentation.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
- 3+ years of experience in DevOps, cloud engineering, or site reliability.
- Proficiency in Azure cloud services (certifications like AZ-400 or AZ-305 are a plus).
- Hands-on experience with Kubernetes, Docker, and container orchestration.
- Strong scripting skills (Python, Bash, PowerShell) and automation tools (Ansible, Terraform).
- Familiarity with AI/ML deployment frameworks (e.g., MLflow, Kubeflow).
- Experience with monitoring, logging, and incident response tools.
- Excellent problem-solving and collaboration skills in a global team.