The Role

We’re looking for a collaborative and motivated DevOps Engineer to join our engineering team. In this role, you’ll help support and scale the infrastructure that powers our healthcare AI platform. You will work on key systems that impact software delivery, cloud infrastructure, and observability, while being supported by senior team members and clear processes.

This is a great opportunity for someone with a solid foundation in DevOps who is excited to grow in a high-impact environment with hands-on experience. You’ll work closely with the engineering, data, and ML teams across the US, India, and LatAm.

Responsibilities

• Configure and deploy cloud services on various cloud providers.
• Manage the Frontera’s Cloud accounts on both AWS and GCP, along with application monitoring and support activities.
• Design, implement, and maintain CI/CD pipelines that enable safe, rapid, and reliable software delivery.
• Automate infrastructure and deployment workflows using Infrastructure as Code (IaC) tools such as Terraform, Ansible, or similar.
• Manage and scale containerized services using Docker and Kubernetes.
• Monitor system performance, availability, and cost, and implement optimizations and improvements.
• Ensure the reliability and uptime of our production environments, including incident response and root cause analysis.
• Work closely with ML team to deploy, monitor, and retrain machine learning models in production environments.
• Lead efforts around cloud cost reporting, optimization strategies, and tooling.
• Ensure systems are secure, compliant, and follow best practices in DevSecOps.
• Contribute to building internal tools and improving developer productivity and observability.

Qualifications

• 4+ years of Software Engineering and Cloud DevOps (AWS/GCP) related work experience.
• Strong proficiency with Terraform for managing cloud infrastructure as code.
• Strong proficiency in Python and scripting languages (e.g., Bash), with an emphasis on automating operations workflows.
• Excellent collaboration and communication skills.
• A pragmatic, ownership-oriented mindset and a desire to build systems that have meaningful impact.
• Experience with modern CI/CD tools (e.g., GitHub Actions, CircleCI, Jenkins, etc.).
• Deep experience with Docker and Kubernetes in cloud-native environments.
• Strong understanding of system administration, networking, and cloud security best practices.
• Experience with monitoring and observability tools such as Datadog, Prometheus, or similar.
• Plus: hands-on experience deploying and supporting machine learning models in production.