Design, develop, and maintain scalable Gen AI applications using LLMs, RAG, and agent-based architectures.
Develop and optimize backend APIs and microservices using Python and relevant frameworks.
Build end-to-end RAG pipelines, including document ingestion, preprocessing, chunking, embeddings, retrieval, and indexing.
Work with vector databases for effective semantic search and context retrieval.
Develop LLM applications using LangChain, LangGraph, and LangFuse.
Implement and deploy LLM solutions using Amazon Bedrock and integrate foundation models into enterprise applications.
Design intelligent AI agents, including tool calling, workflow orchestration, memory, and multi-step reasoning patterns.
Develop effective system prompts and context-engineering strategies to improve accuracy, relevance, and reliability of Gen AI applications.




Implement SSO-based authentication and authorization for enterprise Gen AI applications.
Containerize applications and services using Docker and support scalable deployment across enterprise settings.
Implement observability and monitoring for APIs, LLM applications, model performance, latency, failures, and usage.
Optimize applications for performance, scalability, reliability, security, and cost efficiency.
Collaborate with architects, data engineers, product teams, and business stakeholders to translate requirements into production-ready AI solutions.
Follow best practices for Gen AI security, data privacy, prompt management, evaluation, and responsible AI.
Troubleshoot production issues and continuously enhance the quality and performance of deployed Gen AI applications.

📌 Gen Ai Developer Contract Hyderabad
🏢 Saaki Argus And Averil Consulting
📍 Hyderabad