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Mahdy Muzzammil

Building scalable backends and agentic workflows

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πŸ› οΈ Technical Skills

  • Languages & Frameworks: TypeScript, Python, Node.js (Express), FastAPI, LangGraph, LangSmith, JavaScript
  • Cloud & Infrastructure: AWS (EC2, ECS, EKS, ELB, S3, SQS, SNS), Docker, BullMQ
  • Databases & Caching: PostgreSQL, MySQL, DynamoDB, Redis (Pub/Sub, Streams), Prisma ORM

πŸš€ Featured Projects

πŸ”΄ Backend Systems

api_monitor β€” TypeScript

Production-grade API monitoring & incident tracking system

  • Queue-first async processing with BullMQ + Redis workers
  • Rolling analytics: 24h/7d/30d uptime, avg latency, p95/p99
  • Incident workflows with OPEN/ACKNOWLEDGED states
  • Webhook alerts with retry/backoff + full Swagger/OpenAPI docs

prokoi β€” Python

Multi-tenant project management backend for organizations

  • API β†’ Service β†’ Repository architecture with FastAPI
  • JWT auth, custom middleware, permission-based RBAC
  • Sprint lifecycle APIs: velocity, workload, team performance
  • Redis Streams + WebSocket real-time notifications

πŸ€– AI & Agentic Systems

Assess-AI β€” Python + TypeScript

Automated evaluation & curriculum-aware teaching assistant

  • Multi-agent LangGraph pipeline: Vision LLM extracts questions, rubrics, solutions, and student answers from uploaded PDFs via a shared graph-builder factory
  • Dual-grader ensemble with strict + fair LLM scoring, confidence aggregation, and per-question iterative persistence
  • GraphRAG syllabus agent combining vector search + entity-relationship graph to power a TA chatbot with curriculum-aware context

EpiTrace β€” JavaScript

Autonomous incident monitoring & remediation backend

  • Designed for "Cline CLI as Infrastructure" workflows
  • Detects, traces, and remediates backend incidents
  • Agentic approach to ops β€” no manual intervention

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