Software Engineer

Abdullah Naseem

Building calm, durable systems that work under pressure.

Profile

About

I'm Abdullah, a software engineer. I'm more interested in what a system does on day 90 than on day 1, the boring-but-load-bearing layer where retries, idempotency, and failure modes decide whether software stays useful or just demos well. Most of my work has drifted from pure backend toward end-to-end development and LLM/agentic systems, and the interesting problems live in the same place: making AI behave in production. Currently building Vendor Master Intelligence at PieCyfer.

Core tools

PythonTypeScriptJavaScriptSQLFastAPIDjangoFlaskNode.jsReactVue.jsTemporalPostgreSQLMySQLSQLAlchemyMongoDBRedisRabbitMQRedashDockersystemdAWSGCPHetznerLLMsRAGAgentsOpenAILangChainLangExtractLiveKitQdrantChromaPandasScikit-learnScrapyPlaywrightSelenium

Selected work

Projects

Vendor Master Intelligence

An AI system that finds what's hiding in messy procurement data — reading 30K+ contracts per client, reconciling them against ERP records, and flagging duplicates, pricing anomalies, and compliance risks. Surfaced over $160K in recoverable savings on the first full run across $2.1B in vendor spend.

PythonTemporalPostgreSQLSQLAlchemyAWSDockerRedashLangExtractGeminiOpenAILLMs

Adaptive E-Learning Platform

A learning platform that turns your own course materials into adaptive quizzes, diagrams, and flashcards on demand. RAG over your documents, multi-model LLM routing, and tool calls that pick the right artifact for whatever you're studying.

FastAPIReactPostgreSQLQdrantMinIORedisGroqHuggingFaceAWSsystemd

Echolet — Voice AI Platform

A full-stack voice agent platform — the kind a real business could pick up tomorrow. Real-time STT/LLM/TTS over LiveKit with multi-turn dialogue, intent classification, call routing, booking flows, and conversation analytics. FastAPI backend, React/TypeScript frontend.

PythonFastAPIReactTypeScriptLiveKitPostgreSQLSQLAlchemyAWSDockerClerkAgents

High-Throughput Scraping Platform

A regional data ingestion pipeline replacing a manual weekly process, someone checking a dozen+ listing sites by hand, with a self-running system that builds the canonical data layer for downstream product analytics. Built on Scrapy for static targets and Playwright (with managed proxies and stealth) for JS-heavy ones, running at 10K+ pages/day at 85%+ extraction accuracy. State-by-state rollout: the initial Texas run pulled 500K+ records into a unified schema; Louisiana is next. The interesting architectural piece is a depth-aware RabbitMQ queue that backpressures crawl rate against MySQL write capacity, so the database never becomes the bottleneck no matter how fast the spiders finish.

PythonScrapyPlaywrightMySQLSQLAlchemyRabbitMQFlaskAWSDocker

Latest writing

View log

18 min read

The model is the easy part

What three months of building a contract-intelligence pipeline taught me about production AI systems.

Trajectory

Experience

PieCyfer

Python Software Engineer

Aug 2025 – Present
  • Built Vendor Master Intelligence — an AI system that audits vendor procurement at scale: extracts 20+ structured fields from contracts, reconciles them against ERP records of 30K+ documents per vendor, and flags duplicates, pricing anomalies, and compliance risks. Surfaced over $160K in recoverable savings on the first full run.
  • Built a high-throughput scraping platform on Scrapy + Playwright across a dozen+ business-listing sources, pulling 10K+ pages/day at 85%+ extraction accuracy with depth-aware RabbitMQ queues, managed proxies, and MySQL/S3 storage.
  • Designed retriggerable ingestion pipelines that continuously process and sync 12K+ contract files, taking reconciliation cycles from weeks to under 48 hours.

Labmise

Backend Developer

Dec 2024 – Sep 2025
  • Owned the full backend stack — auth, file processing, storage, and LLM integrations.
  • Built and shipped autonomous agents, including a multi-turn voice agent that swaps between LLM providers.
  • Cut API response times by 35% with query tuning and caching.
  • Worked on architecture changes that took roughly 20% off feature rollout time.

Broadstone Technologies

Backend Intern

Jul 2024 – Nov 2024
  • Refactored event-processing logic to drop full-table scans, cutting compute spend and improving response times by 70%.
  • Built Flask and Python backend services for cloud event tracking and log retrieval.
  • Wrote webhook pipelines for S3, GitHub, Dropbox, Slack, and Google Drive integrations.
  • Used RabbitMQ and MongoDB for async event handling.

Softturf

Backend Intern

Jun 2023 – Sep 2023
  • Built Django and DRF REST APIs for auth, the product catalog, and order workflows.
  • Set up automated email notifications to lift customer engagement.
  • Added role-based access control on sensitive endpoints.

Foundation

Education

University of Management and Technology, Lahore

Bachelor of Science in Software Engineering

2021 – 2025