Monitor database and system performance using CloudWatch metrics, alarms, and logs; troubleshoot proactively.
Develop, deploy, and optimize AI/ML solutions using AWS AI services including SageMaker and Bedrock, supporting model training, inference, and integration into production systems.
Automate operational tasks using AWS Lambda, Systems Manager (SSM), and Infrastructure-as-Code tools such as CloudFormation or Terraform.
Design, build, and maintain scalable, fault-tolerant data processing and analytics workflows on AWS using services such as API Gateway, S3, EC2, RDS, Lambda, Glue, Athena, DynamoDB, EMR, Kinesis, DataSync.
Design and integrate agentic AI systems, including LLM-based agents, multi-agent workflows, and autonomous orchestration pipelines using frameworks such as LangChain and LangGraph.
Implement ETL/ELT pipelines and data architectures that support machine learning, analytics, and intelligent agent-based applications.
Support CI/CD pipelines for AI models and data workflows using Jenkins and container-based platforms such as ECS, EKS, or Kubernetes.
Apply security best practices across AI and data platforms, including IAM least-privilege access, encryption, audit logging, and compliance controls.
Maintain technical documentation for AI architectures, data pipelines, infrastructure configurations, and operational runbooks.
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