DevOps Engineer

About the Role

We need a DevOps Engineer to build and manage the infrastructure powering our AI products and client platforms. You'll design CI/CD pipelines, manage Kubernetes clusters, set up monitoring and alerting, and build the MLOps infrastructure that keeps our AI models running reliably in production. We work across AWS and Azure, deploy with Docker and Kubernetes, and increasingly need infrastructure that supports GPU workloads, model serving, and real-time data pipelines.

What You'll Do

• Design and manage cloud infrastructure on AWS and Azure using IaC (Terraform, Pulumi)
• Build and maintain CI/CD pipelines for application and ML model deployment
• Manage Kubernetes clusters and containerized workloads
• Set up comprehensive monitoring, logging, and alerting (Datadog, Grafana, CloudWatch)
• Build MLOps pipelines for model training, versioning, and serving
• Implement security best practices including secrets management and network policies
• Optimize infrastructure costs and performance across environments
• Automate operational tasks and incident response procedures

What We're Looking For

• 4+ years of DevOps/SRE/Platform engineering experience
• Strong expertise with AWS (EC2, ECS, EKS, Lambda, S3, RDS) or Azure equivalent
• Experience with Infrastructure as Code (Terraform, Pulumi, or CloudFormation)
• Proficiency with Docker and Kubernetes in production
• Experience building CI/CD pipelines (GitHub Actions, GitLab CI, or Jenkins)
• Strong Linux administration and scripting skills (Bash, Python)
• Understanding of networking, DNS, load balancing, and CDN configuration
• Experience with monitoring and observability platforms

Nice to Have

• Experience with MLOps (SageMaker, Vertex AI, MLflow)
• Familiarity with GPU infrastructure and model serving (Triton, TensorRT)
• Experience with cost optimization tools and FinOps practices
• Knowledge of service mesh (Istio, Linkerd)
• Experience managing multi-cloud or hybrid cloud environments

Tech Stack