Muhammad Faisal

I’m a backend-focused full-stack engineer with 4+ years building and scaling production systems across AI pipelines, analytics, high-volume messaging, and third-party integrations. I specialize in Django, database performance, Celery-based workflows, and AWS deployment, with hands-on React delivery.

At Evolve Edge, I optimized the highest-traffic APIs of a large-scale production platform—cutting the main listing endpoint from 9s+ to under 2s with ~97% fewer database queries and eliminating an ~80% CPU spike in a daily scheduled job. I also built an LLM-powered pipeline that converts user messages into structured, validated alerts (type, severity, confidence, reasoning), driving hundreds of production alerts triaged at over 95% staff acknowledgement plus 100K+ LLM-generated summaries. In parallel, I engineered timezone-aware Celery/Twilio messaging workflows with batch scheduling, delivery callbacks, retries, campaign tracking, and opt-out compliance, delivering ~200K messages per month and millions lifetime across 200K+ enrollments.

I’m equally motivated by systems that need to be both efficient and reliable: I built an internal natural-language analytics service with a query planner routing questions across PostgreSQL and MongoDB using guarded read-only queries, hybrid joins, and result-size limits. I also architected a memory-efficient streaming pipeline for large Zoom and Teams meeting recordings—extracting audio via FFmpeg and uploading via S3 multipart without buffering whole files in memory—so downstream transcription and sales-call analysis can run smoothly. On the product side, I delivered staff-facing React interfaces including dashboards, campaign configuration, review panels, MFA flows, and audit-log views.