Gen AI Engineer

Generative AI Development

• Design and build AI-powered chatbots and conversational assistants using LLMs.
• Develop solutions using AWS Bedrock models including Anthropic Claude Sonnet.
• Implement Retrieval Augmented Generation (RAG) architectures for enterprise knowledge retrieval.
• Integrate LLMs with enterprise data sources such as databases, APIs, document repositories, and knowledge bases.

AWS AI Platform Development

• Develop AI applications using AWS Bedrock, SageMaker, Lambda, API Gateway, Step Functions, and S3.
• Build scalable Python-based microservices using FastAPI or similar frameworks.
• Expose AI capabilities as secure APIs through AWS API Gateway for internal and external consumers.
• Implement authentication, rate limiting, and secure API access patterns.

Conversational AI Engineering

• Design conversational workflows and prompt engineering strategies.
• Manage session context and multi-turn interactions for chatbot applications.
• Implement guardrails to mitigate hallucinations and enforce enterprise policies.

Data & Knowledge Integration

• Build ingestion pipelines for structured and unstructured data including PDFs, documents, and databases.
• Implement vector search and knowledge retrieval systems using OpenSearch, Pinecone, FAISS, or similar technologies.

AI Operations & Monitoring

• Monitor model performance, latency, and usage costs.
• Implement logging, evaluation frameworks, and observability for LLM-based systems.
  • Continuously improve prompt strategies and retrieval pipelines.