Python, vector stores, data pipeline development, retrieval strategies, re-ranking, multi-step agent workflows, embedding models, prompt engineering, RAG architectures

Databases, API design, Distributed Systems, Python, LangChain, CrewAI, LLMs, AutoGen, backend architecture, LlamaIndex

RAG, Python programming language, AWS AI ML services ecosystem, FAST APIs, Machine Learning architectures

Etl, Sql, Databricks, ELT, Python, Data Modelling, Spark, cloud-native data services, CI CD, warehousing concepts, containerisation, AI coding tools, GitHub Copilot, Claude Code

Deep learning architectures (CNNs, Exploratory Data Analysis (EDA, probability , Python, Sql, Tensorflow, Etl, Pytorch, Nosql, XGBoost, Azure ML, RNNs, Statistics, Vertex AI, MLflow, Kubeflow, linear algebra, Data annotation tools, Scikit-learn, MLOps workflows, Data preprocessing, Feature engineering, Distributed training and scaling ML on large datasets, ML model evaluation, Transformers

Rust, AWS, Cloudformation, FastAPI, Kubernetes, Python, Azure, Gcp, Terraform, Jenkins, Git, Spark, Go, vLLM, GitHub Actions, MLflow, Hugging Face Transformers, LangChain, TorchServe, TF Serving, CI CD pipelines