Java, Distributed Systems, Spring Boot, LangChain, LangGraph, Vector Databases, DeepEval, AI evaluation frameworks, event-driven architectures, RAG pipelines, API ecosystems

Rpa, Ansible, Prometheus, Dynatrace, Bash, Datadog, Python, LangChain, ITSM APIs, LlamaIndex

Api Integration, Python, LangChain, CrewAI, ethical AI principles, LLMs, reasoning algorithms, Planning Systems, reinforcement learning, prompt engineering, AutoGen, tool augmentation, fine-tuning techniques, safety mechanisms, agentic frameworks, AI ML frameworks

Sql, MLops, Python, LangChain, CrewAI, Generative AI, AI Solution Development, AutoGen, OpenAI, llamacpp, LlamaIndex, Prompt Engineering, Langraph

Python, AWS, Agentic AI frameworks, Agent orchestration on cloud platforms, RAG Retrieval-Augmented Generation, MLOps best practices, semantic search, Low-code No-code agent building, CI CD pipelines, Azure Cognitive Search, Microsoft Bot Framework, Azure Cognitive Services, Google Perplexity

Typescript, Python, AWS, Google Cloud, Azure, orchestration patterns, multi-agent architectures, AI governance guardrails, microservices-based architectures, Agentic AI systems, AI services, model evaluation, responsible AI practices, CrewAI, Generative AI, LLMs, RAG vector databases, Microsoft Foundry, cloud platforms, Monitoring, agent frameworks, Langgraph, performance optimization, context engineering techniques, Google ADK

batch vs. real-time inference, Python, CrewAI, LangChain, GenAI, ML infrastructure, GPU management, vector databases, embedding models, vLLM, Llm, LangGraph, AutoGen, Ollama, TGI, Milvus, RAG pipelines, ChromaDB, Weaviate, model serving, AI ML systems

prompt pipelines, LLMs, tool calling, agent orchestration frameworks, RAG, AI-powered features