AI Development Lifecycle (AI DLC, MLops, AWS AI services, Deployment, Monitoring, Continuous Improvement, LLMOps, Gemini models, Copilot Chat, Amazon Bedrock, Amazon Nova, Model evaluation, Amazon Titan, Amazon Q Developer, Anthropic Claude, GitHub Copilot, Prompt engineering

software engineering practices , Bash Scripting, Version Control Tools, automation, Git, Computer Vision, Python Programming, Deep Learning, semantic segmentation, YOLO, object detection models

snowflake , bedrock , Scikit Learn, Python, XGBoost, Data Cloud, agentic frameworks, MCP, langchain, large enterprise datasets, analytics platforms, ML libraries

XGBoost, Python, Tensorflow, Amazon SageMaker, LightGBM, Scikit-learn

Azure Cloud, Tensorflow, Machine Learning, Azure Functions, Pytorch, Python, Nlp, Azure ML, Azure DevOps, FAISS, MLOps tools, MLflow, Kubeflow, Scikit-learn, LLM-based systems, vector databases, Azure ML pipelines, Weaviate, Pinecone, HuggingFace, Spacy, Transformers

Api Integration, Pytorch, Tensorflow, Python, Azure ML, model observability, LangChain, Hugging Face, data ingestion, GCP Vertex AI, AWS SageMaker

Sql, AWS, FastAPI, Python, Docker, Multi-Agent Systems, Agent Frameworks, LLM API Integration, OpenSearch, Prompt Engineering, Skill Building, Guardrails, pgvector, RAG Pipelines, Pinecone