- Extensive hands-on experience with AWS Bedrock Agents including action groups, knowledge bases, and orchestration patterns </p> - Strong expertise in RAG architectures with proven experience extending to agentic workflows </p> - Proficiency in AWS Lambda development with Python, including complex event-driven architectures </p> - Deep knowledge of AWS API Gateway for REST and WebSocket APIs, including custom authorizers and integration patterns </p> - Experience with AWS Fargate for containerized workloads and long-running agent processes </p> - Strong expertise in AWS CDK (TypeScript or Python) and CloudFormation for infrastructure automation </p> - Deep Knowledge and experience of vector databases and semantic search integration with Bedrock knowledge bases </p> - Experience with both SQL databases (RDS, Aurora) and NoSQL solutions (DynamoDB) </p> - Understanding of prompt engineering, function calling, and agent reasoning patterns </p> - Proficiency in CI/CD pipelines for serverless applications and container deployments </p> - Strong problem-solving abilities with systematic approaches to distributed system challenges </p> - Excellent communication skills to explain complex AI architectures to diverse audiences </p> Technical Qualifications </p> - Bachelor's or Master's degree in Computer Science, Information Technology, or related technical field </p> - Minimum 1 years of hands-on experience with Generative AI and LLM-based solutions </p> - Proven experience architecting and deploying serverless applications on AWS at scale </p> - Demonstrated expertise building RAG systems and extending them to agent-based architectures </p> - Strong track record with AWS CDK/CloudFormation for complex multi-service deployments </p> - Experience with Bedrock Agents in production environments </p> </div></span> </body> </html>"