Implement and maintain cloud infrastructure using infrastructure-as-code.
Support and improve CI/CD pipelines for application and ML workloads.
Operate containerized workloads in Kubernetes or managed container platforms.
Assist in rolling out platform improvements and infrastructure changes.
Automate repetitive operational tasks using scripts and tooling.
Assist with deploying and monitoring AI/ML workloads.
Use AI-assisted tools to improve Log analysis and alert triage, Incident investigation and documentation, Deployment validation and testing.
Participate in on-call rotations
Respond to and help resolve environment & CI/CD pipeline incidents.
Monitor system health using dashboards, logs, and alerts.
Contribute to post-incident reviews and follow-up actions.
Follow and contribute to established DevOps standards and practices.
Document procedures, runbooks, and operational knowledge.
Strong interest and motivation to grow technical skills.

2-4+ years of experience in DevOps, Cloud, SRE, or Infrastructure Engineering.
Experience with at least one cloud provider (Azure, AWS, or GCP)
Hands-on exposure to:
Scripting experience (Bash, Python, or similar)
Infrastructure as Code (Terraform, IaC 2.0, or similar)
CI/CD pipelines
Containers (Docker) and Kubernetes concepts
Monitoring, logging, and alerting tools.
2+ years in healthcare technology or other highly regulated SaaS environments (financial services, government)
Familiarity with AI-driven monitoring or AIOps tools.
Experience using AI-assisted development or operations tools.
Understanding of cloud networking and security fundamentals.
Experience supporting on-call.

Education

Bachelor's degree in Computer Science, Computer Engineering, or related technical field
Advanced certifications (AWS/GCP/Azure professional-level, CKA, CKS, CISSP) are highly valued
Demonstrated commitment to continuous learning

Intermediate DevOps Engineer, AI-Enabled

Key skills