quantitative analytics , Retrieval-Augmented Generation (RAG), SAS, SQL Server, Sql, Deep Learning, MLops, Machine Learning, Excel, Oracle, Python, Prompt engineering, Statistical methods, Teradata, Gen AI, R

snowflake , Oauth, Dynamodb, Sql, Nosql, Concurrency, Terraform, Python, AWS, Airflow, Distributed tracing, Async programming, GRPC, GitHub Actions, Event-driven processing, dbt, CI/CD, Observability, OIDC

secure coding , Automated Testing, DevSecOps, AWS ECS, Agile Methodologies, Python, LLM orchestration layers, cloud-native deployments, vector databases, CI CD, data sensitivity considerations, AI-assisted software development tools, MCP-based tool integrations, RAG pipelines

Natural Language Processing (NLP), Testing, Git, Docker, Kubernetes, LangChain, Crew.ai, vector databases, embedding models, knowledge retrieval systems, modern software development practices, prompt engineering, Autogen, development frameworks, Advanced Python programming, LLM optimization techniques, CI/CD, async programming, RAG pipelines

Python, Sql, Statistical Analysis, model evaluation, integration components, orchestration systems, machine learning methods, Data Validation, AI solutions

Tensorflow, Django, Pytorch, Reactjs, Flask, FastAPI, Python, LangChain, RAG Retrieval Augmented Generation, Pinecone, Azure OpenAI, LangGraph, Vector Databases, Chroma, FAISS, OpenAI, ML frameworks, Generative AI LLMs, Gemini, Prompt Engineering