Java, Google Cloud Platform, Graphql, PostgreSQL, REST, metrics, MongoDB, Azure, Kubernetes, AWS, logs, Event-driven systems, Vector databases, traces, GRPC, Cloud Monitoring, Cloud-native infrastructure, TimescaleDB

Java, Machine Learning, Kafka, Tensorflow, Hive, Pytorch, Spark, Kubernetes, Python, Airflow, Ray, Kubeflow

Java, Cloud Infrastructure, Python, AWS, embeddings, LLMs, Go, RAG-based systems, vector databases, GenAI systems, multimodal AI pipelines, AI ML systems

Databases, React, Node.js, Python, MCP Model Context Protocol, LLM integration, Cloud-native development, Workflow automation

Microservices, Docker, Python, MLops, Rest Apis, Kubernetes, embeddings, fine-tuning concepts, vector databases, Pinecone, Responsible AI practices, RAG implementations, LangGraph, model evaluation, ChromaDB, Azure AI Search, LangChain, CrewAI, Semantic Kernel, prompt engineering, AutoGen, FAISS, Weaviate, LlamaIndex

AWS, Kubernetes, Python, Sqs, Kinesis, Docker, Elasticsearch, Kafka, Weaviate, Pinecone, FAISS

Deep Learning, Numpy, Pytorch, Opencv, Python, Seaborn, Computer Vision, Matplotlib, scikit-image, LSTM, PIL

Java, Graphql, Scala, Kafka, TigerGraph, MLops, Docker, Neo4j, XGBoost, Spark, Kubernetes, Python, AWS, Airflow, pgvector, Qdrant, LightGBM, Go, MLflow, Flink, Neptune, Kubeflow, Milvus

snowflake , Java, Github, Jira, Jenkins, Confluence, Python, data preprocessing, Automation BOTs, Agents, Copilot, GenAI capabilities, N-Tier architectural concepts, Agile development methodology, model evaluation techniques, CI CD pipelines, feature engineering