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

Retrieval-Augmented Generation (RAG, Python, C#, C++, Numpy, Pandas, MLops, Etl, Pytorch, Orchestration, AI coding assistants, Evaluation, Agentic AI solutions, OpenAI-compatible APIs, LLMOps, Azure OpenAI, Data pipelines, LangChain, Embeddings, Vector search, Tool calling, Anthropic Claude, LangGraph

Tensorflow, MLops, Pytorch, XGBoost, Python, Generative AI, AI Agents, Scikit-learn, Conversational AI, Prompt Engineering

data engineering , Apis, Agile Development Methodologies, Microservices, System integration, MLops, Microsoft Azure, AWS, Agentic AI orchestration, Prompt engineering, DevOps practices, Vector databases, AWS Developer CLI, Cloud-native architectures, Agentic AI-based solutions, Continuous integration for AI models, Real-time data processing, Fine-tuning LLMs

.NET, Apis, Agile, Angular, AI integration

Python, Sql, Sklearn, Containers, Gcp, AWS, Azure, LLMs, Pipelines, LlamaIndex, chatbots, model registry, structured outputs, feature pipelines, statsmodels, experiment tracking, embeddings, drift monitoring, LangChain, RAG, analytics agents, NL2SQL pipelines, CI/CD, tool function calling, Forecasting

Apis, Performance Testing, UI, test automation frameworks, Data Validation, ML models, model performance testing