FullStack AWS AI Engineer

• The role involves designing, developing, and deploying full-stack cloud-native applications integrated with Generative AI and Agentic AI solutions using AWS services, while ensuring scalability, security, performance, and production-grade delivery in an enterprise environment.

Requirement/Must Have:

• Strong experience in full-stack development (frontend and backend).
• Hands-on experience with AWS cloud services and cloud-native architecture.
• Experience building or integrating Generative AI or Agentic AI solutions.
• Strong proficiency in Python or similar backend programming language.
• Experience with REST APIs, microservices, and asynchronous processing.
• Experience with containerization using Docker and orchestration using ECS/EKS.
• Strong understanding of CI/CD and DevOps practices.
• Experience working in Agile development environments.

Experience:

• Experience building production-grade enterprise systems.
• Experience working with AI/ML pipelines and cloud-based AI services.
• Experience in designing scalable and resilient distributed systems.

Responsibilities:

• Design, develop, and deploy Agentic and Generative AI solutions using AWS AI services such as SageMaker, Bedrock, Rekognition, Textract, Transcribe, and Translate.
• Integrate LLMs and foundation models into enterprise applications using AWS Bedrock or custom model endpoints.
• Build AI pipelines for inference, prompt orchestration, fine-tuning, and evaluation.
• Implement responsible AI practices including governance, explainability, bias mitigation, and auditability.
• Architect and deploy cloud-native solutions using AWS services such as EC2, Lambda, ECS/EKS, API Gateway, S3, DynamoDB, RDS, Aurora, and Step Functions.
• Implement Infrastructure as Code using CloudFormation, CDK, or Terraform.
• Build and manage CI/CD pipelines using GitHub Actions or AWS CodePipeline.
• Optimize performance, scalability, cost, and reliability using AWS best practices.
• Implement security best practices including IAM, KMS, VPC design, and encryption.
• Set up monitoring, logging, and alerting using CloudWatch, X-Ray, and OpenSearch.
• Support production environments including troubleshooting and performance tuning.
• Collaborate with stakeholders to translate business problems into technical AI solutions.

Should Have:

• Experience with responsible AI practices and model governance.
• Strong understanding of software design patterns and system scalability.
• Experience with financial or regulated enterprise environments.
• Knowledge of advanced AWS architecture and optimization techniques.

Skills:

• AWS cloud services (SageMaker, Bedrock, Lambda, ECS/EKS, etc.).
• Generative AI / Agentic AI development.
• Full-stack development.
• Python and backend development.
• Microservices and REST APIs.
• Docker, CI/CD pipelines.
• Terraform / CloudFormation / CDK.
• Monitoring tools (CloudWatch, X-Ray, OpenSearch).
• Data pipelines and AI model integration.

Qualification And Education:

• Bachelor s degree in Computer Science, Engineering, or related field preferred.