process mining , Ibm Watson, Cloud, MLops, multi-agent orchestration, Claude, Business Process Mapping, Responsible AI frameworks, LLM architecture, Azure AI Copilot, GenAI architecture, IT enterprise architecture concepts, Google Vertex AI, observability, API-first, AI architecture, prompt engineering, agentic workflows, RAG, MCP, cloud AI platforms, AI governance, Gemini, Amazon Bedrock

.NET, Python, Evaluation frameworks and metrics for AI systems, AI observability monitoring, Vector databases, LLM orchestration, RAG architectures

S3, RDS, Dynamodb, React, Lambda, CloudFront, Docker, ECS, FastAPI, Python, Api Gateway, AWS, LangChain, LLMs, monitoring frameworks, DevOps practices, Vector Databases, Embeddings, CI CD pipelines, GenAI integrations, RAG, Prompt Engineering, LlamaIndex

MLops, compliance alignment, agent workflow orchestration, evaluation dataset design, defining guardrails standards, LLMOps, AI GenAI architecture patterns, corpus preparation, prompt lifecycle management, CI CD, Security-by-design, network boundaries, monitoring approach, embedding design, retrieval strategy, Data strategy architecture, Governance guardrails, model registry, deployment strategy, Access Control, solution reference architectures

data quality assurance , object storage , Kafka, Azure DevOps, Azure, Jenkins, Spark, AWS Bedrock, Feast, distributed query engines, OpenAI, Amazon Deequ, Data Architecture for AI, cloud native ETL, DataHub, Apache Atlas, Power BI with Copilot, LangChain, CrewAI, data lakehouses, LangGraph, GitHub Actions, ELT frameworks, platform integration, Vertex AI, Great Expectations, Google ADK, Evidently, AutoGen

lifecycle management , privacy compliance , leanix , MLops, Identity, auditability, versioning, agentic AI, explainability, generative AI, LLMOps, Reliability, data foundations, Monitoring, Evaluation, Security, model risk, Responsible AI, architecture standards

.NET, Azure, Python, OpenAI API, Langchain

MLops, Docker, Flask, System Design, FastAPI, Kubernetes, Python, Api Development, Generative AI, Agentic AI

resiliency , Cloud security, Containers, Serverless Computing, Gcp, Data Warehouse, Identity Management, Microservices, AWS, Streaming, Kubernetes, Enterprise Architecture, Azure, Cloud Architecture, Apis, AI orchestration frameworks, GenAI, Vector databases, LLMOps, Customer 360, RAG, GenAIOps, Lakehouse, AI Architecture, Master Data Management, Cloud governance, Event-driven architecture, Observability

Tensorflow, Pytorch, MLops, Python, Machine Learning Algorithms, LangChain, model governance, Generative AI, HuggingFace, vector databases, prompt engineering, AI Agent frameworks, RAG pipelines