AI Architect

Design and implement LLMbased applications RAG pipelines agentic workflows finetuning prompt engineering

Integrate foundation models via Amazon Bedrock and manage model selection guardrails and evaluation

Build and optimize vector search and retrieval pipelines Amazon OpenSearch Kendra or thirdparty vector DBs like Pinecone on AWS

Implement agent orchestration frameworks LangChain LangGraph Bedrock Agents for multistep reasoning tasks

Build scalable APIs and microservices using Python FastAPIFlask or Nodejs

Implement data pipelines with AWS Glue EMR or native Python ETL for training inference data prep

Manage containerized workloads via ECSEKS

Build responsive UIs that consume backend AI services

Implement Realtime streaming responses for chatstyle AI interfaces

Integrate authentication Amazon Cognito and rolebased access control

Architect solutions using core AWS services Bedrock SageMaker Lambda API Gateway S3 DynamoDB RDSAurora ECSEKS Step Functions

Set up CICD pipelines CodePipeline CodeBuild or GitHub Actions AWS deploy

Manage cost optimization for AI workloads token usage monitoring model routing caching strategies via ElastiCache