Senior AI-Enabled DevOps Engineer

Responsibilities

• Design, implement, and operate cloud-native infrastructure for production workloads.
• Build and maintain CI/CD pipelines for applications and ML systems.
• Develop and manage infrastructure-as-code to ensure consistency, scalability, and repeatability.
• Improve deployment reliability through automation, testing, and rollout strategies.
• Support AI/ML workloads, including model deployment, scaling, and monitoring.
• Integrate AI-assisted tools into DevOps workflows to improve alert quality and noise reduction, incident triage and root-cause analysis, capacity planning and performance optimization.
• Design and maintain observability solutions using metrics, logs, and traces.
• Participate in on-call rotations and lead incident response for complex issues.
• Continuously improve system resilience through proactive automation.
• Partner with application, platform, and data teams to deliver reliable systems.
• Provide technical guidance and code reviews for devops team members.
• Contribute to architecture discussions and influence technical direction within your domain.
• Document standards, runbooks, and best practices.

Requirements

Must-haves

• 5-8+ years of progressive experience designing and implementing large-scale, automated infrastructure and CI/CD Pipelines.
• Strong experience with cloud platforms (AWS, GCP, or Azure).
• Hands-on expertise in cloud-native architectures and microservices.
• Infrastructure as Code (Terraform, IaC 2.0, etc.).
• Containers and Kubernetes.
• CI/CD systems (GitHub Actions, GitLab CI, Jenkins, ArgoCD).
• Strong knowledge-level of CI/CD best practices, GitOps workflows and deployment strategies (blue/green, canary).
• Proficiency in scripting or programming (Python, Bash, Go, etc.).
• Demonstrated ability to write custom scripts for deployment, monitoring and system tasks.
• Experience with monitoring, logging, and alerting tools (Prometheus, Grafana, ELK, Datadog).
• Exposure to AI/ML workloads.
• Strong knowledge of containerization and orchestration (Docker, Kubernetes).
• Solid understanding of networking, security principles, and high-availability architectures.

Nice-to-haves

• 3+ years in healthcare technology or other highly regulated SaaS environments (financial services, government).
• Experience with AI-driven monitoring or AIOps tools.
• Knowledge of cloud cost optimization strategies.
• Advanced certifications: AWS Certified DevOps Engineer-Professional, Microsoft Certified DevOps Engineer Expert, Certified Kubernetes Administrator (CKA).
• Experience with security automation and DevSecOps practices.