Google Cloud Platform (GCP), Large Language Model (LLM) native metrics, Python, LangGraph, Observability frameworks, Evaluation pipelines, Vector databases, RAG-like architectures, Multi-agent systems, Granular tracing, CrewAI ADK

Java, Node, Typescript, Python, Git workflows, agent orchestration patterns, Go, model routing, Mobile, MCP and SDK-based integrations, CI CD, context engineering, Cost Optimization, testing strategies, modern agentic IDEs, prompt design, LLM mechanics, evals

Python, multi-agent systems, vector databases

graph databases , Retrieval-Augmented Generation (RAG) solutions, Machine Learning, Artificial Intelligence, C++, Tensorflow, Pytorch, Python, Boolean operations, Generative AI, Geometric transformation algorithms, AI Agents, 3D geometry, Vector databases, Claude, Microservices-based architecture, Reporting libraries, Coordinate systems, OpenAI, Vector mathematics, Prompt Engineering

Pytorch, Python, multi-GPU sharding, TensorRT-LLM, SAM, open-weight foundation models, agentic AI, Hugging Face ecosystem, LLMs, quantisation, Grounding DINO, SGLang, vLLM, DINOv2, Distillation, VLMs, large vision models, MCP

Java, Node, Typescript, Python, Git workflows, agent orchestration patterns, Go, model routing, Mobile, MCP and SDK-based integrations, CI CD, context engineering, Cost Optimization, testing strategies, modern agentic IDEs, prompt design, LLM mechanics, evals

Retrieval-Augmented Generation (RAG), Spring Boot, Angular, Microservices, React, Typescript, Javascript, Docker, Python, AWS, Java, Node.js, Google Cloud, Cloud Applications, Git, FastAPI, Restful Apis, Azure, Kubernetes, Context Engineering, RAG pipelines, AI agent frameworks, Generative AI, LLMs, DevOps practices, Agent Harness frameworks, CI/CD pipelines, AI agents, Prompt Engineering

DevSecOps, Python, AWS, testing strategies, observability