workflow engines , Python, tool function calling, tracing observability tooling, Logfire, AI systems in production, prompting, Temporal, OpenTelemetry, pydantic-ai, LiteLLM, MCP, agent architectures

Pytorch, Python, EDA Tools, Scientific Computing, Spice, reinforcement learning

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

Machine Learning, Deep Learning, Microservices, Python, CrewAI, Generative AI, Agentic AI frameworks, Prompt engineering, LLMs, LangGraph, AutoGen, Vector Databases, Model evaluation techniques, RAG architectures

Amazon Web Services (AWS), Large Language Models (LLMs), Machine learning frameworks and libraries, Developing and deploying AI models in production environments, Python Programming Language, Cloud computing concepts and services

Retrieval-Augmented Generation (RAG), MLops, Docker, Python, AWS, LangChain, GenAI, Generative AI, AWS Bedrock, Prompt engineering, Model monitoring, SageMaker, Vector Databases, OpenAI APIs, Containerized deployments, LLM evaluation

Databases, Apis, Microservices, Python, Machine Learning, Predictive Analytics, Computer Vision, AI application architecture, LLMs, cloud platforms, Agentic AI solutions, AI integrations, Generative AI applications, AI ML frameworks, Forecasting, Ontology and Knowledge Representation, embedding, RAG vector databases, AI-powered search, IoT Connected Systems, Knowledge Graphs