- Build and manage database platforms including Amazon RDS, Aurora, DynamoDB, Neptune, and ElastiCache.

- Implement identity and security solutions using IAM, IAM Identity Center, AWS Organizations, KMS, Secrets Manager, GuardDuty, Inspector, Security Hub, WAF, Shield, and CloudTrail.

- Monitor cloud environments using Amazon CloudWatch, CloudWatch Logs, AWS Config, X-Ray, and EventBridge.

- Develop cloud governance, compliance, auditing, and operational standards.

- Implement logging, monitoring, alerting, and observability solutions.

- Optimize AWS environments for performance and operational excellence.

- Perform cloud cost optimization using AWS Cost Explorer, Trusted Advisor, Savings Plans, Reserved Instances, and tagging strategies.

- Build automated provisioning and deployment pipelines using DevOps methodologies.

- Develop CI/CD pipelines using GitHub Actions, GitHub, TeamCity, Jenkins, CodePipeline, CodeBuild, and CodeDeploy.

- Manage containerized applications using Docker, Amazon ECS, AWS Fargate, Amazon EKS, and Kubernetes.

- Collaborate with development, security, infrastructure, and architecture teams for cloud adoption initiatives.

- Troubleshoot production incidents and perform root cause analysis.

- Support disaster recovery, backup strategies, and business continuity planning.

- Maintain cloud documentation, architecture diagrams, and operational runbooks.

- Drive platform stability, lifecycle management, environment provisioning, upgrades, and infrastructure automation.

AI & Machine Learning Responsibilities :

- Enable enterprise AI capabilities on AWS.

- Design and implement AI-powered cloud solutions using Amazon Bedrock.

- Build generative AI applications leveraging Large Language Models (LLMs).

- Work with Amazon SageMaker for model training, deployment, and inference.

- Integrate Amazon Textract for intelligent document processing.

- Utilize Amazon Q for developer productivity and enterprise AI use cases.

- Build AI-ready cloud platforms supporting APIs, Model Context Protocol (MCP), integrations, and reusable AI services.

- Implement governance, security guardrails, auditing, compliance, and monitoring for AI workloads.

- Collaborate with AI engineering teams to operationalize machine learning solutions in production.

- Design scalable AI infrastructure supporting enterprise workloads.

Required Technical Skills :

AWS Core Services :

- Amazon EC2, AWS Lambda, Amazon S3, Amazon EBS, Amazon EFS, Amazon VPC, Route 53, Elastic Load Balancer (ALB/NLB), Auto Scaling, CloudFront, API Gateway, RDS.

- Performance optimization skills.

- Excellent communication and stakeholder management skills.

- Experience working in Agile/Scrum environments.

Mandatory Certifications :

- Candidates must possess at least one active AWS Associate-level or higher certification.

Preferred Skills :

- Experience with enterprise cloud transformation programs.

- Experience implementing FinOps and cloud cost optimization strategies.

- Exposure to serverless architectures.

- Knowledge of AI governance and responsible AI practices.

- Experience with Generative AI platforms and LLM integrations.

- Experience working with large-scale distributed systems.

- Exposure to multi-account AWS environments using AWS Organizations and Control Tower.

- Strong analytical and problem-solving abilities.

- If you're passionate about AWS Cloud, Platform Engineering, Cloud Modernization, Infrastructure Automation, and AI-powered cloud solutions, we'd love to hear from you. Immediate joiners are highly preferred.