large language models (LLMs), multi-agent workflows, embedding-powered retrieval solutions, GenAI-based systems

software engineering practices , Large Language Model (LLM) applications, Retrieval-Augmented Generation (RAG), Apis, Microservices, MLops, Python, AI development frameworks, LLMOps, architecture patterns, semantic models, prompt engineering, cloud environments, agentic AI architectures, DataOps, knowledge and context graphs, CI/CD, modern AI methodologies, cloud-native development

Python, Databricks, Sdlc, System Design, AWS, FastAPI, LLMs, Multi-agent orchestration, AI agent development, Semantic Kernel, Azure AI Foundry, Vector search systems, Production grade scalable AI systems, Enterprise AI platforms, LangChain, Agentic AI, Generative AI, LangGraph, Cloud native architectures, Embedding pipelines, Transformers

Nlp, Distributed Systems, Cursor, GitHub Copilot, LLMs

large language models (LLMs), Python, Sklearn, FastAPI, LangChain, CrewAI, Hugging Face Transformers, generative AI solutions, Plotly, Vapi, TRL, Salesforce AgentForce, Google Agent SDK, OpenAI Agent SDK, Microsoft Copilot, Dialogflow

Tensorflow, Pytorch, Gcp, Flask, Microservices, AWS, FastAPI, Kubernetes, Python, Azure, Docker, Apis, event-driven architecture, AI orchestration frameworks, LLMs, OpenAI, LlamaIndex, Hugging Face, Azure OpenAI, embeddings, CI CD, LangChain, RAG, MLflow, vector search, Scikit-learn, Anthropic, prompt engineering

Tensorflow, Unsupervised Learning, Kafka, Machine Learning, Deep Learning, Pytorch, XGBoost, Distributed Systems, Python, Kubernetes, Docker, Spark, scikit-learn, ML ecosystem, gradient boosting, Flink, containerisation, LLM APIs, clean code, MLflow, embedding-based systems, ClickHouse, supervised learning, LightGBM, model evaluation, RAG architectures, gRPC APIs, prompt engineering

Cursor, Nlp, Distributed Systems, GitHub Copilot, LLMs