Cloud platforms (Azure preferred), Lakehouse architectures (Databricks), Large Language Models (LLMs), Apache Spark, Sql, Tensorflow, Pytorch, Python, Machine Learning Algorithms, MLflow, MLOps practices, Prompt engineering, GenAI application development, Vector databases, Model versioning, Monitoring and drift detection, Agentic AI workflows, Multi-LLM orchestration systems, Statistical Modeling, Distributed computing frameworks, Deep learning frameworks, Embedding models, Automated retraining, CI/CD for ML, Semantic search architectures

Numpy, Pandas, Pytorch, Python, LangChain, Anthropic Claude, LangGraph, AI coding assistants, Azure OpenAI

Devops, Jenkins, Git, Docker, Kubernetes, Python, AgenticAI frameworks, R, AI ML engineering, CI CD tools

Cassandra, PostgreSQL, Spring Boot, Microservices, Rest Api, Nosql, React, Javascript, MySQL, Python, AWS, Java, Sql, Figma, Gcp, MongoDB, Azure, Opik, Claude, LangGraph, Multi-Agent Systems, evals, Traces, Langsmith

model selection , Backend Development, Distributed Systems, Llm, Evaluation Frameworks, Prompt Engineering, AI Infrastructure

data engineering , state management , Java, Amazon Web Services, Machine Learning, Python, Orchestration, quality evaluation, applied artificial intelligence, retrieval, tool-enabled workflow automation, re-ranking, Indexing, cloud-native services, grounding methods, embedding-based search

Tensorflow, Pytorch, Python, Machine Learning, Artificial Intelligence, Azure, AWS, Langchain, Hugging Face, LangGraph, RAG