Machine Learning, Performance Engineering, Microservices, Scalability, Numpy, Docker, Distributed Systems, Python, AWS, Api Development, Pandas, MLops, Kubernetes, Prompt engineering, Reliability, MLflow, multi-agent orchestration frameworks, Embeddings, ML pipelines, Autonomous workflow design, Kubeflow, Generative AI, RAG architecture, LLMOps, Vector databases, Scikit-learn, AI evaluation and monitoring frameworks, distributed systems architecture

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

data engineering , Metadata Management, Cloud Services, Testing Frameworks, Data Quality, MLops, Data Governance, Data Ingestion, Data Observability, AI Enabled Analytics, Generative BI, Embedding Pipelines, Ai, AI Assisted Analytics, Data Platforms, Distributed Data Systems, Cloud Data Certifications, Feature Stores, Governance Platforms, Metadata Lineage, Data Validation

Restful Apis, Microservices, Python, distributed application architectures, Agentic AI architectures, Infrastructure as Code, AWS CDK, event-driven systems, Amazon Bedrock, AWS cloud-native services

Java, Api Integration, Tensorflow, Gcp, Pytorch, MLops, Azure, Python, AWS, LangChain, GenAI, Vector databases, Hugging Face, Pinecone, Llm, LangGraph, microservices architecture, FAISS, RAG, Azure AI Search, Weaviate