Key skills
AIMLOpenAIRAGMLOpsMLflowAWSAzureTerraformKubernetesDockerGitHub ActionsEKSAKSCloudFormationIAMSageMakerBedrockAPI GatewayAzure DevOpsGitHubCI/CDCloud Security
About this role
Versaterm is a global public safety solutions company that is dedicated to enhancing community safety through innovative technology. They are seeking a Senior DevOps/MLOps Engineer to contribute to their cloud infrastructure, MLOps tooling, and CI/CD pipeline implementations.
Responsibilities:
- 5+ years experience in cloud infrastructure (AWS and/or Azure)
- Strong hands-on experience with Kubernetes (EKS or AKS)
- Strong hands on experience to the cloudl infrastructure
- Experience deploying production-grade APIs (API Gateway/APIM)
- Experience with managed AI services (Bedrock, Azure OpenAI, SageMaker, Azure ML)
- Experience implementing CI/CD pipelines (GitHub Actions, Azure DevOps, etc.)
- Strong understanding of IAM, RBAC, and cloud security best practices
- Experience with containerization (Docker) and infrastructure-as-code (Terraform, Bicep, or CloudFormation)
- Experience building or operating an internal developer platform
- Experience with MLOps tooling (MLflow, model registry, evaluation pipelines)
- ISO, SOC, NIST framework familiarity
- Experience implementing RAG architectures and vector databases
- Experience implementing AI governance, logging redaction, and content filtering
- Multi-cloud architecture experience
Requirements:
- 5+ years experience in cloud infrastructure (AWS and/or Azure)
- Strong hands-on experience with Kubernetes (EKS or AKS)
- Strong hands on experience to the cloud infrastructure
- Experience deploying production-grade APIs (API Gateway/APIM)
- Experience with managed AI services (Bedrock, Azure OpenAI, SageMaker, Azure ML)
- Experience implementing CI/CD pipelines (GitHub Actions, Azure DevOps, etc.)
- Strong understanding of IAM, RBAC, and cloud security best practices
- Experience with containerization (Docker) and infrastructure-as-code (Terraform, Bicep, or CloudFormation)
- Experience building or operating an internal developer platform
- Experience with MLOps tooling (MLflow, model registry, evaluation pipelines)
- ISO, SOC, NIST framework familiarity
- Experience implementing RAG architectures and vector databases
- Experience implementing AI governance, logging redaction, and content filtering
- Multi-cloud architecture experience