Design, deploy, and maintain ML and GenAI platforms using
Azure AI, Azure ML, Databricks, AKS, AWS SageMaker, Bedrock, Lambda
, etc.
Manage
CI/CD pipelines
via Azure DevOps or AWS CodePipeline.
Implement
Infrastructure as Code (IaC)
using
Terraform, ARM/Bicep, CloudFormation
.
Integrate cloud databases (
Azure SQL, Cosmos DB, AWS RDS, DynamoDB, S3
) with AI/ML services.
Oversee
governance, audit, observability, and compliance
across ML ecosystems.
Ensure
security best practices
including IAM, RBAC, Azure Policy, AWS SCPs, and least privilege principles.
Manage
networking, load balancing, VPNs, VNets, DNS
, and related services.
Enable
ML lifecycle management
– deployment, retraining, drift monitoring, and model evaluation.
Apply
unit and integration testing
within CI/CD pipelines.
Collaborate with data scientists for efficient
end-to-end ML workflows
.

Required Skills:

Azure & AWS AI Services:
Azure AI Foundry, OpenAI, Bedrock, Anthropic Claude, LangChain, LlamaCloud.
Security & Compliance:
Token usage, prompt injection risks, jailbreak mitigation, AI Red Teaming, Azure AI Evaluation SDK.
Programming:
Python (TensorFlow, PyTorch, scikit-learn), Bash, PowerShell.
Containers & Orchestration:
Docker, Kubernetes.
Monitoring Tools:
Grafana, Prometheus, Application Insights, Azure Monitor.
IaC & Automation:
Terraform, ARM/Bicep, CloudFormation, AWS CDK.
Good to Have:
Azure Bot Framework, APIM, Application Gateway, GitHub Copilot, Cursor, Claude Code, M365 Copilot.

More Jobs at Aaspire Data Services

ML Ops Lead Engineer

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