Most AI demos die in staging. Mine run in production, serving millions of users, processing millions of records, and earning revenue.
Who I am
I'm a Full Stack AI Engineer with 5+ years building enterprise-grade AI systems. Not Jupyter notebooks. Not proof-of-concepts. Real pipelines, real users, real outcomes.
I own the full path: data ingestion, RAG retrieval, multi-agent orchestration, and production deployment, with the reliability, observability, and compliance posture enterprise systems actually demand.
I lead AI and backend engineering for production systems and I'm open to Senior AI Engineer, AI Architect, and founding engineer roles. Open to relocation: UAE, GCC, Europe, Malaysia.
What I've shipped
Designed Graph and Contextual RAG on Azure AI Search delivering 35% higher retrieval groundedness vs baseline vector search, with p95 query latency under 800ms across a 100,000+ document corpus at enterprise scale.
Built autonomous decision pipelines using LangGraph running concurrent production workloads, fully traced in LangSmith. Standardized reusable agent templates that cut average feature delivery time by 40%.
Built a LangSmith observability pipeline with continuous groundedness monitoring and automated alerting that cut production silent-failure rate by 50%, giving engineering teams full visibility into LLM behavior in production.
Designed and shipped an async batch ETL pipeline across 5+ heterogeneous data sources with intelligent job scheduling, delivering 60% lower data refresh latency and enabling real-time analytics on enterprise datasets.
Led a zero-downtime migration merging 2 live B2B platforms into a single Django system serving millions of active users. Delivered on schedule with zero production incidents over a 12-month engagement.
Built a Redis caching layer that delivered 40% faster API responses and eliminated redundant LLM inference calls, directly lowering monthly inference spend for a high-traffic production system.
Built 3 real-time social and networking apps on Django REST featuring WebSocket chat, Agora video calling, push notifications, and activity feeds serving concurrent live users. Added one-tap sign-in via JWT and OAuth2 across 4 providers.
Modeled multi-stage factory production logic in Django covering takt time, machine routing, buffers, and assembly workflows across 5 product configurations. Eliminated 8+ hours per week of manual reporting with automated PDF and Excel analytics exports.
Tools & technologies
AI & Machine Learning
Backend Development
Cloud & DevOps
Databases & Data
Standards & Compliance
Career history
Background
AWS Educate Certifications