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Building backends that think & systems that scale.

  • πŸ€– Β  Architecting LLM-powered applications with RAG pipelines and vector search
  • βš™οΈ Β  Backend engineering with Python, Flask, Django & REST APIs
  • 🧩 Β  Consistent DSA practice β€” Arrays, Trees, Graphs, Dynamic Programming
  • 🌱 Β  Currently deepening expertise in DevOps & Cloud Infrastructure
  • πŸ’Ό Β  Open to full-time roles & internships β€” Sayakmitra16@gmail.com

γ€” About Me 〕

class SayakMitraMajumder:
    role        = "AI Engineer Β· Backend Developer Β· Systems Builder"
    university  = "KIIT University β€” B.Tech, CSE (Communication Engineering)"
    focus       = ["LLM Applications", "RAG Pipelines", "Scalable Backend Systems"]
    building    = "AI-powered applications at the intersection of NLP and engineering"
    interests   = ["FinTech", "Product-Based Companies", "Distributed Systems"]
    languages   = ["Python", "Java", "JavaScript", "C++", "SQL"]

I architect backend systems powered by AI β€” from RAG-based retrieval pipelines to REST APIs built for production scale. My work sits at the intersection of Language Models, system design, and clean backend engineering.

γ€” Tech Stack 〕

My Skills

Specialized in: LLM APIs Β  RAG Pipelines Β  Vector DBs (Qdrant) Β  REST API Design Β  Prompt Engineering

γ€” Featured Projects 〕

πŸš€ Student's Corner β€” AI-Powered Career & Learning Platform Β  [ Flagship ]

A modular multi-agent AI platform delivering personalized career preparation, code intelligence, and adaptive learning workflows through orchestrated AI pipelines.

πŸ—οΈ Architecture & Backend

  • Engineered a modular FastAPI backend with a shared database/repository layer powering multiple independent AI agents from a single service layer
  • Integrated Spring Boot middleware handling authentication, resume parsing, and backend request orchestration between frontend and AI services
  • Designed persistent session architecture with MongoDB-backed pipeline and state storage, including interrupted-session recovery and graceful resumption

πŸ€– AI Orchestration

  • Built a unified platform integrating three specialized agents: AI Interviewer, Code Reviewer, and Adaptive Roadmap Generator β€” each operating as an isolated, stateful pipeline
  • Implemented multi-model orchestration across OpenAI, Anthropic (Claude), and ElevenLabs APIs, routing to the appropriate model per agent's task profile
  • Engineered a graph-based roadmap generation pipeline with dynamic node updates, progress tracking, and version restoration support


πŸ€– AI Portfolio Maker

LLM-powered backend that auto-generates personal portfolio sites

  • Prompt-engineered generation pipeline with context-aware LLM calls
  • RAG architecture using vector embeddings for personalized content retrieval
  • REST API layer with structured output parsing and template rendering

Python Flask LLM APIs Qdrant RAG

AI-driven adaptive learning platform with performance analytics

  • Adaptive assessment engine that adjusts difficulty based on learner response patterns
  • Real-time feedback pipeline integrated into a multi-subject student dashboard
  • Modular backend architecture designed for extensibility across content domains

Python AI/ML REST APIs Backend

Content-based recommendation engine using feature similarity

  • TF-IDF vectorization and cosine similarity for accurate content matching
  • Efficient pandas-based data pipeline processing 5,000+ movie records
  • Clean inference interface designed for API integration

Python Pandas NumPy Scikit-learn

Role-based backend banking application with full CRUD operations

  • Enforces role-based access control across customer and admin tiers
  • Transaction integrity maintained with relational schema and constraint validation
  • Structured Java OOP design with clean separation of service and data layers

Java SQL OOP RBAC

γ€” Problem Solving 〕

Platform Focus Areas Profile
LeetCode Arrays Β· HashMaps Β· Stacks Β· Queues Β· Trees Β· Graphs ReversibleWizard

Consistent practice in data structures and algorithms with emphasis on time/space complexity optimization and clean problem decomposition.

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γ€” Certifications 〕

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Open to Backend / AI Engineering roles Β· Full-time Β· Internships Β· Collaborations


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Building systems that think. Architecting backends that scale.

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