Software Engineer building distributed systems & AI-native infrastructure

I design systems that scale under load and stay correct under concurrency.

I design and ship production-grade backend systems focused on:

• High-concurrency distributed architectures
• Idempotent APIs & transactional guarantees
• Event-driven AWS infrastructure
• Database performance at scale
• AI-native pipelines (LLM + RAG + document intelligence)

I care deeply about correctness, scalability, and business impact.

_{NodeJS   Django   Python   JavaScript   Docker   Redis   PostgreSQL   MongoDB   AWS}

Architecture: S3 → Lambda → SQS → Lambda → PostgreSQL
Scale: 10,000+ async jobs/day

Designed and implemented a fault-tolerant, event-driven ingestion pipeline to process large CSV datasets into PostgreSQL.

Engineering Highlights

• Queue-based isolation for failure containment
• Idempotent job processing to prevent duplicate writes
• Transaction-safe inserts with DB constraints
• Designed scaling roadmap for 10M+ rows using Step Functions + Glue

Focus Areas: Reliability • Concurrency Control • Horizontal Scalability

📖 Architecture Blog • 🎥 Demo

An AI-powered system that extracts structured quantitative metrics from complex PDF reports (tables + vector charts).

Stack: FastAPI • Celery • PostgreSQL • Layout Parsing Engine • LLM Orchestration

Core Capabilities

• Layout-aware PDF parsing engine
• Hybrid extraction pipeline (tables + vector-based charts)
• Confidence scoring for extracted metrics
• Source-of-truth tagging with page-level traceability
• Modular pipeline architecture (worker + service layer separation)

Designed for extensibility and large-scale document ingestion workflows.

GitHub • Demo

A monitoring platform that tracks website changes and generates AI summaries for competitive intelligence.

Stack: React • FastAPI • PostgreSQL • Snapshot Engine

System Design Highlights

• Versioned website snapshots
• Structured diff detection engine
• AI-generated change summaries
• Scalable content monitoring workflow

Focused on automated intelligence extraction from dynamic web content.

🌐 Live • GitHub

A developer productivity CLI tool for schema-driven dataset generation using LLM workflows.

Stack: Python • LLM APIs • CLI Automation

Capabilities

• Schema-based synthetic data generation
• Automated dataset creation for rapid prototyping
• Extensible command-line interface
• AI-assisted developer workflow acceleration

GitHub

Distributed payment architecture with strong transactional guarantees.

Stack: Java • Spring Boot • PostgreSQL

Engineering Highlights

• ACID-compliant transaction management
• Service isolation for payment consistency
• Modular microservice architecture
• Database-level consistency enforcement

Designed to simulate production-grade financial backend behavior.

GitHub

High-read performance backend optimized for feed delivery at scale.

Stack: Node.js • PostgreSQL • Redis

System Highlights

• Feed query optimization
• Redis-based caching strategy
• Normalized relational schema design
• Improved read performance under load

Built with scalability and cache efficiency in mind.

GitHub

Backend Engineering • Distributed Systems • AI Infrastructure
Remote-first teams • UAE product companies