data engineering , Github, Data Modeling, Distributed Systems, Python, AWS, Performance Tuning, Azure ML, Git, Gcp, Azure Cloud services, Azure, IoT Hub, Event Hub, AuthN, CI CD, Optimization, AuthZ, SQL databases, security best practices, NoSQL databases, cloud platforms, Stream Analytics, batch streaming pipelines, AI ML solution development

Java, Regression Testing, Python, cost latency monitoring, vector search, orchestration patterns, tool function calling, trace inspection, structured output generation, AI systems, context engineering, agent frameworks, AI-native developer tools, agentic workflows, MCP Model Context Protocol, evaluation systems, LLM application patterns, RAG, reranking, prompt design, observability

Ml, Api Integration, Nlp, Python, GenAI, LLMs, Ai, voice bots, backend systems, chatbots, RAG, AI agents

Nlp, AI principles, programming languages relevant to AI development, DevOps practices for AI, deep learning for computer vision, prompt engineering, machine learning models

Java, Github, PostgreSQL, Pl Sql, Spring Boot, Jira, Jacoco, Angular, Jenkins, Git, Docker, Sonarqube, Oracle, Python, Ai, GitLab CI

Orchestration, Tensorflow, Pytorch, Containers, Python, embeddings, experiment tracking, RAG systems, monitoring solutions, Hugging Face, vector databases, prompt optimization, CI CD pipelines, MLOps tooling, model registries, evaluation frameworks

Apis, LangChain, data pipelines, LLMs, n8n, Flowise, Zapier, automation workflows, no-code tools, AI agents

React, Typescript, Azure cloud services, FastAPI, Python, GitHub Actions, Agent frameworks, Advanced prompt engineering, RAG and vector databases