Git, Docker, Python, LangChain, LangGraph, Agentic AI, Multi-Agent systems

Spark, Azure, Python, AWS, Airflow, cloud ML platforms, MLFlow

Java, Rest Apis, Generative AI, AI evaluation methodologies, Python APIs, Prompt Management, Vector Databases, Agentic AI, Production-grade AI Agents, Multi-Agent Systems, AI ML technologies, Prompt Engineering, Data ingestion pipelines

Jira, Azure ML, Jenkins, Git, Confluence, Databricks, Rest Apis, Python, RAG workflows, CrewAI, LLMs, AI Agents, PydanticAI, event-driven architectures, Codeium, AutoGen, LangGraph, WebSockets, GitHub Copilot, Windsurf

Github, BigQuery, Google Cloud Platform, PostgreSQL, Jira, Django, Cloud Storage, FastAPI, DataFlow, Python, LangChain, vector databases, Cloud Run, Vertex AI, AI agents, GenAI orchestration frameworks, RAG pipelines, Google ADK

FastAPI, LangChain, embedding pipelines, idempotency, message queues, Anthropic APIs, distributed systems patterns, Pinecone, prompt engineering, AutoGen, LangGraph, Python 3.10, asyncio, FAISS, Vertex Matching Engine, structured logging, event-driven architecture

Tensorflow, Numpy, Git, Pandas, Pytorch, MLops, Docker, Databricks, Azure, Python, AWS, LangChain, Transformers, LLMs, scikit-learn, Hugging Face, retrieval-augmented generation, MLflow, CI CD

Data Science, Python, LangGraph, Statistical Modeling, Agentic Workflows using LangChain-based agents, Fine-tuning techniques for LLMs, Transformer architecture

Machine Learning, Databricks, Kubernetes, Python, AI ML engineering concepts, containerisation, CI CD, prompt engineering, cloud-native deployment, AI coding tools, RAG, agentic frameworks, Large Language Models