BigQuery, PostgreSQL, Dataproc, Redis, Nosql, MLops, Docker, Spark, Apache Beam, DataFlow, Kubernetes, LangChain, LangGraph, OpenTelemetry

Machine Learning, Git, Docker, Pyspark, Python, Sql, DataFrame APIs

test automation, Jenkins, Typescript, Python, Test Architecture, Playwright, API contracts, prompt engineering, service boundaries, GitHub Actions, LLM applications, RAG, backend code, context retrieval agents

.NET Framework, Agent2Agent (A2A), Model Context Protocol (MCP), C#, Tensorflow, Pytorch, Python, Azure Cosmos DB, MLops, Azure, vector search, NoSQL document databases, Agent Development Kit, LTI, scikit-learn, LangGraph, Vertex AI, Azure AI Search, prompt engineering, LMS plug-ins, xAPI, infrastructure-as-code, CI/CD, Microsoft Agent Framework, container orchestration, relational SQL database design and querying

containerization , Sparql, Rdf, Docker, Python, Oauth2, Azure, SHACL, Lang Chain, Lang Graph, Security, CI CD, Agentic frameworks, LLM orchestration, Evaluation, IEC 61850, Cloud and infra-Azure, COMTRADE, Vector databases, Production-grade async clean APIs, Knowledge graphs, RAG, Local LLM inference, OIDC

Api Management, Uipath, Aws Services, Power Automate, Functions, Rpa Tools, Lambda, Docker, Api Gateway, AWS Bedrock, AKS, Azure OpenAI, AI automation architectures, Azure services, Microsoft Power Platform, CI CD pipelines, container orchestration

Tensorflow, Numpy, Pytorch, Docker, XGBoost, Python, Pandas, MLops, Azure Machine Learning, scikit-learn, vector databases, Azure AI Foundry, LangGraph, Azure AI Search, Application Insights, LangChain, experiment tracking, RAG architecture, LLMOps, Azure OpenAI Service, LightGBM, embedding models, Semantic Kernel, CI/CD pipelines, Azure AI Content Safety, Azure App Service Functions

software engineering practices , Apis, MLops, Microservices, Python, DataOps, LLMOps, architecture patterns, prompt engineering, cloud-native development, AI development frameworks, agentic AI architectures, knowledge and context graphs, semantic models, modern AI methodologies, cloud environments

production readiness , Python, ML training and evaluation workflows, scalable system design, data pipelines, GenAI LLM application development, deployment observability, model pipelines, APIs and backend services, ML LLM framework