Java, Typescript, Python, observability for AI systems, validation-before-action patterns, orchestration tool-calling, RAG, LLM agent frameworks, retrieval architecture evaluation

large language models (LLMs), multi-agent orchestration frameworks, GenAI-powered systems, vector-based retrieval

Hld, Lld, Solid Principles, AWS, embeddings, system design fundamentals, chunking strategies, hybrid retrieval, vector databases, tool calling MCP, RAG pipelines, retrieval data layer, agent loops, BM25, LLM agent systems, code-intelligence tooling, AST-based chunking, rerank, LLM-driven graph extraction

Sql, Test Cases, Rest Apis, Node.js, Python, Nosql, LangChain, function calling, access-control, tool integration, multi-agent workflows, audit-logging, AI security, vector databases, evaluation harnesses, embedding-based search, prompt engineering, LLM orchestration, LangGraph

data engineering , react.js , Data Modelling, Azure Data Bricks, Microservices, Data Quality, Typescript, Distributed Systems, Rest Apis, Python, LLMs, RAG systems, vector databases, agent frameworks, AI integration, large-scale data processing, ETL pipelines

production deployment , Accessibility, API design, Application Architecture, Typescript, Javascript, Scalability, Python, Testing, Java, Kotlin, Version Control, System Design, Performance, Agentic systems, Operational monitoring, Go, Data science outputs, Model APIs, Security, Service-oriented architectures, CI CD, Code review practices, Production Support, Data integration patterns, Observability, Intelligent automation, LLM-powered workflows, Documentation, Reliability