Mohammed Rayaan Pasha

Product Manager

Bengaluru, Karnataka, India0 mo experience
AI EnabledAI ML Practitioner

Key Highlights

  • Expert in backend architecture for scalable applications.
  • Proficient in AI integration for practical applications.
  • Achieved sub-50ms synchronization in containerized environments.
Stackforce AI infers this person is a Backend-focused Developer with expertise in AI and microservices architecture.

Contact

Skills

Core Skills

Node.jsAi IntegrationPostgresql

Other Skills

AlgorithmsCDatabase PartitioningExpress.jsJavaJavaScriptMERN StackMySQLNatural Language ProcessingOpenAI APIPHPPredictive AnalysisPrisma ORMPythonRabbitMQ

About

I am a Developer with focus on Distributed Systems and AI Integration. I don't just build UI!! I enjoy architecting the backend logic that keeps applications fast and scalable. What I'm building right now: - Microservices: designing event-driven architectures using Apache Kafka or RabbitMQ. - AI Tools: Creating practical LLM applications, like Natural Language-to-SQL tools and automated marketing agents. - Performance: Obsessing over latency...recently achieved sub-50ms synchronization in a containerized environment. I often use themes from my favorite movies and sitcoms to make my coding projects more engaging. I believe software should have personality. Core Stack: TypeScript, React, Node.js, PostgreSQL, Docker, Redis, Kafka Check out my code: https://github.com/mdrayaanpasha

Experience

Gauge.ro

Full-Stack Developer Intern

Apr 2025Nov 2025 · 7 mos

  • Saved 5+ marketing hours/week by building a generative AI marketing module using OpenAI API.
  • Reduced infrastructure cost by 23% after migrating backend from strapi CMS to custom express js endpoints
  • Improved Manual Entries by 35% by developing a CRM with automated workflow.
OpenAI APIExpress.jsNode.jsAI Integration

Royal & co

Full Stack Developer Intern

Dec 2024Feb 2025 · 2 mos · Bengaluru, Karnataka, India

  • Enabled 8+ non technical people to query database by building a Natural Language-to-SQL tool using LLMs
  • Improved query read times by 12% after implementing database partitioning.
  • Reduced billing and analysis time by 18% after developing a billing system with predictive analysis
Natural Language ProcessingDatabase PartitioningAI IntegrationPostgreSQL

Education

St Joseph's University

Bachelor of Computer Applications

Jul 2024Mar 2027

Cathedral Composite PU College & High School

Class 11 & 12 — CS + Commerce

Jul 2022Mar 2024

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