Technology, AI-AI Engineering, AI/ML Solution Architecture and Design

Cloud deployment, Cloud Devops, Microservices, Git, Docker, Rest Apis, Enterprise Integration, Python Full-Stack Development, Agentic AI LangChain LangGraph MCP RAG, AI Frameworks, CI CD, LLM Prompt Engineering, Agentic AI Concepts, Testing Observability, GenAI LLM solutioning, Security Responsible AI

Machine Learning, Python, Ontology and Knowledge Representation, AI application architecture, LLMs, RAG vector databases, Agentic AI solutions, AI integrations, embedding, AI-powered search, Knowledge Graphs, Generative AI applications, AI ML frameworks

Ml, Flows, Mobile Application Development, Cursor, APEX, Salesforce platform architecture, agentic tool-use patterns, agentic systems architecture, cloud-native architecture, Ai, Claude, prompt engineering, platform scalability principles, Lightning Web Components, LLM orchestration, integration patterns, Gemini, AI developer assistants

AWS), Cloud technologies (Azure, Java, Katalon, Saas, JIRA, Web Services, Jmeter, Restassured, Confluence, Swagger, Web Applications, Postman, Python, SOAP APIs, Context design, AI prompt engineering, Models evaluation, Programming/scripting languages, CI/CD, AI Generative AI, Github source control

Distributed Systems, LangChain, policy enforcement, LLMs, agent orchestration frameworks, LangGraph, ML platforms, cost controls, model adapters, embeddings pipelines, stateful workflow design, vector DBs, external APIs, RAG retrieval, observability

snowflake , Machine Learning, Tableau, Python, Azure DevOps, Statistical Analysis, Power Bi, Bi Tools, Sql, Automated Testing, Azure ML, Git, MLops, Databricks, Time-series models, Model deployment, Optimization, Feature engineering, Llm, ML pipelines, Monitoring, Forecasting, Generative AI, Decision Support, Ai, anomaly detection, Machine Learning frameworks, Data exploration, Agentic AI, RAG, CI/CD, Azure AI