Amazon Web Services, Apis, Microservices, MLops, Distributed Systems, Microsoft Azure, Kubernetes, LangChain, CrewAI, GenAI, RAG embeddings, LLMs, LLMOps, prompt engineering, AutoGen, agentic AI systems, evaluation frameworks, cloud AI platforms

.NET, containerization , Java, Apigee, Python, LangChain, Big Query, vector search, Cloud Spanner, Cloud Functions, fine-tuning, data pipelines, GKE, model training, RAG patterns, multi-cloud environments, Istio, Pinecone, Pub Sub, FAISS, Weaviate, GCP services, Fire store

model selection , Api Management, Microservices, Kubernetes, LangChain, embeddings, fine-tuning, Azure OpenAI, Semantic Kernel, prompt engineering, Caching, inference optimization, cloud-native architectures, Azure AI Search, semantic search, knowledge grounding, Microsoft Azure stack

vectorization , Tensorflow, Gcp, Pytorch, MLops, Docker, Azure, Kubernetes, Python, AWS, Data lakes, Generative AI, Transfer Learning, LLMs, Azure OpenAI Service, Fine-Tuning, Embedding models, Google Vertex AI, RAG, Data pipelines, Amazon Bedrock, Transformer architectures

snowflake , Java, Devops, Azure, Python, AWS, Generative AI, vector databases, RAG pipelines, prompt engineering

Python, BigQuery, FastAPI, LangGraph, Pub Sub, LLM Orchestrator, A2A, Cloud Run, LLDs, HLDs, Vertex AI, Gen AI Prompt Engineering, Google Vertex AI, Pydantic, AI standards and protocols, cloud-native architectures, LangChain, Enterprise Architecture Design Patterns, LLMOps, ACP, Semantic Kernel, reference architectures, RAG Pipeline, MCP, Responsible AI, FastMCP

.NET, Design Patterns, Solid Principles, Enterprise Integration, Python, Agentic AI Design, Dataverse, Graph API, RAG AI Agents, Azure OpenAI, Azure AI Services, Dynamics, Sharepoint, Azure Cloud Application Development, Prompt Engineering

python, Javascript, MLops, Cicd, Kubernetes, generative AI, Llm, AI solution architect

Responsible AI frameworks, AI Architecture, Agentic AI architectures, LLMs and SLMs