- 5+ years of software development experience with strong hands-on expertise in Python .
- Strong hands-on experience in Generative AI and LLM application development .
- Strong hands-on experience with Amazon Bedrock and foundation models.
- Hands-on experience with RAG (Retrieval-Augmented Generation) architecture.
- Experience with Prompt Engineering and prompt optimization .
- Experience with embeddings, vector databases, semantic search, and vector search .
- Experience developing AI Agents / Agentic AI solutions using Amazon Bedrock.
- Experience with Amazon Bedrock Knowledge Bases, Agents, and Guardrails .
- Experience with LangChain, LlamaIndex, LangGraph, or equivalent GenAI frameworks .
- Experience integrating GenAI applications with REST APIs, enterprise applications, databases, and document repositories .
- Strong knowledge of AWS services , including S3, Lambda, API Gateway, IAM, CloudWatch, and OpenSearch.
- Strong SQL and data-processing skills .
- Experience with Git, CI/CD, Docker, and AWS cloud deployment .
- 5+ years of software development experience , with strong Python expertise.
- Proven hands-on experience building and deploying production-grade GenAI/LLM applications using Amazon Bedrock .




- Robust understanding of Bedrock foundation models, model invocation, inference parameters, and prompt-based application development .
- Hands-on experience building RAG solutions using Bedrock Knowledge Bases, embeddings, and vector search .
- Hands-on experience developing Bedrock Agents / Agentic AI solutions and integrating agents with enterprise tools and APIs.
- Strong understanding of Prompt Engineering, LLM evaluation, hallucination reduction, and response optimization .
- Experience implementing Bedrock Guardrails and AI safety controls.
- Strong experience with AWS cloud architecture and services required for GenAI solutions.
- Experience with API integration, databases, document repositories, and enterprise systems .
- Understanding of AI security , including prompt injection, data leakage prevention, IAM, authentication, authorization, and secure API integration.
- Experience with LLM observability, application monitoring, logging, performance optimization, and token/cost management .
- Ability to design and develop scalable, secure, reliable, and production-ready GenAI solutions .

📌 GENAI Developer with AWS Bedrock (Hyderabad)
🏢 Brace Infotech Private
📍 Hyderabad