Key Responsibilities

- Design, implement, and maintain AWS infrastructure supporting production-grade GenAI solutions.
- Architect cloud solutions using AWS services including:
- AWS Lambda
- API Gateway
- DynamoDB
- Amazon S3
- Amazon Bedrock
- Amazon SageMaker
- IAM

- Develop and maintain Python-based reusable cloud and GenAI platform components.
- Build, manage, and optimize Infrastructure-as-Code using Terraform.
- Develop and maintain CI/CD pipelines using GitHub Actions.
- Implement secure IAM policies, access controls, and governance standards.
- Monitor cloud environments using CloudWatch, X-Ray, logging, and observability tools.
- Troubleshoot infrastructure, deployment, security, and application issues.
- Optimize cloud infrastructure for performance, reliability, scalability, and cost efficiency.
- Collaborate with Data Science, MLOps, DevOps, and Engineering teams to operationalize GenAI models and services.
- Develop reusable cloud patterns, architecture standards, and operational documentation.

Must-Have Skills

AWS Cloud Engineering

- Strong hands-on experience with:
- AWS Lambda
- API Gateway
- DynamoDB
- S3
- IAM
- CloudWatch

- Experience designing and supporting production AWS environments.





Generative AI Platforms

- Experience working with:
- Amazon Bedrock
- Amazon SageMaker

- Understanding of GenAI application deployment and operationalization.

Infrastructure as Code

- Strong expertise in:
- Terraform

- Experience building reusable infrastructure modules and automation frameworks.

DevOps & CI/CD

- Strong experience with:
- GitHub Actions
- CI/CD pipelines
- Automated deployments

- Understanding of DevOps best practices and cloud automation.

Programming & Automation

- Robust proficiency in:
- Python

- Experience building automation scripts and cloud platform components.

Security & Operations

- Experience implementing:
- IAM policies
- Security controls
- Monitoring and observability solutions

- Knowledge of cloud governance and compliance practices.

Good-to-Have Skills

- Experience with:
- MLOps platforms and workflows
- Containerization technologies (Docker, Kubernetes)
- Serverless architectures

- Exposure to:

- AI/ML model deployment
- FinOps and cloud cost optimization

- AWS certifications preferred.

📌 AWS Cloud Engineer - Chennai/Pune/Bangalore/Hyderabad/Delhi (Telangana)
🏢 Tata Consultancy Services
📍 Telangana