MLops, LLM engineering, AI ML engineering, data privacy and ethical considerations, CI CD pipelines, autonomous AI multi-agent systems, AI observability, AI security solution development

Microservices, MLops, Distributed Systems, Kubernetes, AWS, Cost optimization strategies, GenAI LLMs, SaaS architecture, DevOps practices, Model training, Deep Learning Containers, Feature engineering, Cloud-native architectures, Data ingestion, CI CD pipelines, AI ML platforms

Data Management, Data Quality, Sap Bods, Data Architecture, Data Governance, Data Integration, data lifecycle management, SAP BusinessObjects Data Services

Togaf, semantic layers, knowledge graphs, OpenAI, data management frameworks, AI Architecture, ontologies, embedding models, vector databases, cloud AI platforms, Amazon Bedrock, Responsible AI frameworks, multi-agent orchestration, Azure AI, LLM SLM selection, RAG architectures, Agentic AI architectures, prompt engineering, Anthropic Claude, Google Vertex AI

Azure Databricks, Gdpr, Data Governance, Model Lifecycle Management, AI Governance, EU AI Act, Risk Management, NIST AI RMF, ISO 42001, Generative AI

Hipaa, Iso 27001, Incident Management, PCI-DSS, Electronic Security Systems, Vendor Management, Cctv, Fire Fighting, Fire Detection, Access Control, Governance, HITRUST

data quality assurance , Metadata Management, Etl Development, Data Modeling, Sql, Spark, Data Governance, Databricks, Data Visualization, Python, AWS, data pipelines, Microstrategy

Azure ML, Databricks, Deep Learning, Machine Learning, MLops, Automation, Kubernetes, Python, Docker, Spark, EKS, Vertex AI, AKS, Cloud-native engineering, Gen AI, Ai, AWS Sagemaker, GKE, Agentic AI