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ADITYA KUMAR

AI Engineer · LLM Systems · Backend APIs · GenAI

Building production-grade AI systems using LLMs, automation, and backend APIs. Specialising in multi-agent architectures, RAG pipelines, and scalable AI SaaS platforms.

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ADITYA KUMAR
AI Engineer // GenAI Systems
Actively Deploying
LocationNIT Delhi
Cohort2022 – 2026
BranchCSE
FocusLLM Systems
StatusAvailable

An AI Engineer focused on building real-world AI systems using LLMs, automation, and backend APIs. Experienced in Python and FastAPI with a track record of deploying scalable, production-grade solutions.

Deep interest in AI SaaS, real-time systems, and multi-agent architectures. Currently pushing the frontier on RAG pipelines, persistent chat memory, and collaborative agent-based problem solving.

221210008@nitdelhi.ac.in +91 75290 74394 linkedin.com/in/aditya-kumar github.com/adityakumar
Capability Matrix

Core_Stack Dashboard

// module_01
Languages
PythonJavaScriptSQL
// module_02
AI / ML Frameworks
PyTorchTensorFlowScikit-learnHugging FaceOpenCV
// module_03
GenAI Systems
LLM APIsPrompt Eng.OllamaRAGLangChain
// module_04
Backend
FastAPIFlaskREST APIsNode.jsNext.js
// module_05
Data & Storage
PostgreSQLFAISSVector DBsTableauPower BI
// module_06
DevOps & Tools
GitDockerLinuxAWSVerceln8n
Active Deployments

Active_Nodes

NODE_001 // 2026Deployed
RAG Document Intelligence System

Retrieval-Augmented Generation system enabling accurate question-answering over documents with semantic search and full source attribution.

  • Semantic search via vector embeddings and FAISS for efficient context retrieval
  • LLM integration generating context-aware responses with source attribution
  • Scalable backend APIs supporting multi-document querying and conversational memory
PythonFastAPIFAISSLLMRAG
NODE_002 // 2026Deployed
AI Chat SaaS Platform

Full-stack ChatGPT-like SaaS with authentication, persistent chat memory, streaming responses, and multi-model support.

  • Backend APIs for real-time conversations, session management and message storage
  • Contextual responses via chat history retrieval from PostgreSQL
  • Streaming responses and multi-model support for improved UX
Next.jsFastAPIPostgreSQLLLMStreaming
NODE_003 // 2026Deployed
Multi-Agent AI System

Planner–Executor–Critic architecture for complex task automation with inter-agent communication and iterative output refinement.

  • Planner, executor and critic agents for coordinated task decomposition
  • Inter-agent communication enabling complex multi-step workflows
  • Iterative output refinement through collaborative problem solving
PythonLangChainLLMMulti-Agent
Credential Verification

Education_Log

Verified
National Institute of Technology Delhi
B.Tech — Computer Science & Engineering
2022 – 2026 // Delhi, India
// Core Focus Areas
Artificial Intelligence & Machine Learning
Data Structures & Algorithms
Backend Systems & API Design
Software Engineering Principles
Certified
Google Data Analytics Professional Certificate
Issued by Google via Coursera
// Skills Covered
SQLPythonTableau Power BIStatisticsEDA A/B TestingRegression Hypothesis TestingData Storytelling
Secure Transmission

Establish_Uplink

Direct channel for communications. Currently open to AI engineering roles, GenAI project collaborations, and research opportunities.

Email221210008@nitdelhi.ac.in Phone+91 75290 74394 LinkedInlinkedin.com/in/aditya-kumar GitHubgithub.com/adityakumar
NodeNIT Delhi, India
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