Numpy, Pandas, Gcp, FastAPI, Azure, Python, AWS, GenAI, embeddings, LLMs, prompt engineering, RAG

Python, LangChain, LLMs Prompt Engineering, Custom Guardrails, Vector Embeddings Semantic Search, MLflow, Multi-Agent Orchestration, LLM Evals, LangSmith, LangGraph, AI Observability Tools, RAG, Agent Engineering

isolation), vLLM), Open-source LLMs (Ollama, Security fundamentals (auth, Cloud deployment, Docker, FastAPI, Python, LangChain, Re-ranking models, Vector databases, LangGraph, secrets, Voice AI pipelines, Hybrid search, CI/CD, RAG pipelines, Multi-agent systems, LlamaIndex

Java, Docker, Node.js, Kubernetes, Python, DevOps practices and tools, Prompt engineering, Generative AI or LLM-based solutions

Docker, MLops, Etl, AWS, Python, Kubernetes, Azure, Gcp, Nlp, LLMs, Transformers, feature store, vector DBs, embeddings, data pipelines, RAG, prompt engineering

Python, AI enabled systems, API based integration development, AI driven services, agentic workflows, LLM powered applications, AI assisted development tools

Python, Agentic systems, Orchestration frameworks, Classical machine learning, Multi-step workflows, information extraction, Document understanding

Apache Spark, ELT, Tensorflow, Pytorch, Gcp, Data Warehousing, Azure, Python, AWS, Etl, LangChain, Generative AI, LLMs, Hugging Face, Pinecone, FAISS, ChromaDB, LlamaIndex, RAG architectures

API design, Iam, Integration, Python, generation, Secrets Manager, evaluation practice, GenAI systems, vector store, embedding, retrieval, multi-step tool-calling, agentic system, RAG pipeline, ingestion

Retrieval-Augmented Generation (RAG), Tensorflow, Pytorch, Gcp, Data Warehousing, Azure, Python, AWS, LangChain, Generative AI, LLMs, Hugging Face Transformers, ETL/ELT Tools, LlamaIndex