Gdpr, Machine Learning, Artificial Intelligence, Google Cloud, ELT, MLops, Cloud Architecture, Data Governance, Microsoft Azure, AWS, Etl, LLMOps, generative AI, data platforms, Warehouses, security governance, lakehouses, data lakes, NIST AI Risk Management Framework, ISO IEC 42001, responsible AI practices

.NET, Spring Boot, CDK, Microservices, Docker, Terraform, Openshift, Python, Azure DevOps, AWS, Java, Node.js, Pulumi, Jenkins, Gcp, Helm, Azure, Kubernetes, GitOps, Azure Arc, GitHub Actions, VMware Tanzu, AI ML platforms, GKE, AKS, Istio, EKS, Linkerd, Cloud-native architecture, AWS Outposts

Dlp, Databricks, Rest Apis, Azure Machine Learning, audit logging, Azure API Management, Microsoft Foundry, FinOps, event-driven patterns, Azure OpenAI, Azure AI Foundry, OAuth 2.0, rbac, least privilege, service principals, Azure AI services, Azure AI Search, managed identities, security and governance controls

Machine Learning, Phoenix, Tensorflow, Pytorch, Gcp, Docker, Azure, Kubernetes, Python, AWS, Langchain, LLM-as-a-Judge, Hugging Face, RAGAs, Gen AI Development, Arize, Vector Databases, Langgraph, MCP

Databases, Cli, Cursor, Programming Languages, Microservices, Gcp, Azure, AWS, full-stack architecture, cloud platforms, Claude, GitHub Copilot, engineering best practices, Amazon Q, frontend frameworks, backend services, AI code assistants, Code Gemini

.NET, Azure, Python, OpenAI API, Langchain

Tensorflow, MLops, Pytorch, Python, Nlp, Machine Learning Algorithms, predictive insights, Q A systems, RAG pipelines, LLMs, fine-tuning LLMs, building scaling and optimizing AI systems, AI agent development, model governance, vector databases, CI CD for ML workflows, LangChain, auto-documentation, oci, HuggingFace, prompt engineering, hybrid multi-cloud architectures, Generative AI