Architecting multi-tenant SaaS platforms, event-driven pipelines, and AI-assisted backend infrastructure — systems that preserve context, automate workflows, and scale under production load.
Provisioning pipelines, tenant isolation, role hierarchies, Azure AD onboarding. Built for dozens of organizations and hundreds of users with zero data bleed.
Webhook ingestion, async processing via AWS Kinesis, Lambda workers, DynamoDB streams. Designed for high-volume, fault-tolerant data pipelines.
RAG pipelines, vectorized knowledge bases, confidence threshold handling, human escalation paths. AI as operational infrastructure — not chatbot demos.
Unified email, WhatsApp, VoIP, and calendar ingestion into a single activity timeline. Context-preserving systems across all customer touchpoints.
Typesense and Meilisearch via Laravel Scout. Full-text discovery systems optimized for 150K+ records with sub-100ms response times.
Microsoft Graph API, Salesforce, Twilio, Airbnb, Booking.com, Guesty PMS, bKash, Stripe. Deep API orchestration across real production systems.
Multi-tenant AI platform integrating Airbnb, Booking.com, and Guesty PMS — automating guest communication with context-aware AI replies and human escalation workflows.
Multi-tenant CRM platform preserving full customer communication context across email, VoIP, WhatsApp, and calendar — synchronized to Salesforce in near real time.
High-performance job aggregator with Typesense-powered full-text search, AI-assisted CV generation, and production infrastructure monitoring via Prometheus + Grafana.
Map the data flows, failure points, and integration contracts before writing a single line. Architecture first, always.
Model everything as events. Build for eventual consistency, queue saturation, and third-party downtime from day one.
Design systems that never lose state — across restarts, retries, or handoffs. Context is the product in operational systems.
PHP-FPM tuning, queue worker sizing, Sentry error capture, Prometheus dashboards. Ship observable from day one.
Strong mathematical foundations informing systems thinking, algorithm design, and data-structure decisions in production engineering.
Build systems, not CRUD apps. Every project is an opportunity to design for scale, observability, and operational clarity from the ground up.
Async processing is not optional. Production systems fail synchronously. Design around queues, retries, and eventual consistency by default.
AI is infrastructure, not a feature. RAG pipelines, confidence thresholds, escalation paths — AI that operates safely inside a larger system.
Context is the product. The highest-value thing a system can do is preserve what happened and surface it at precisely the right moment.
"Abul Hassan is a key team member who consistently pushes the boundaries of his skills. He is always digging deep into programming languages and frameworks, such as Laravel, learning new paradigms, understanding the inner workings, and aligning with the latest innovations."
"Another excellent quality he possesses is taking the initiative. He is never afraid to pursue an unknown feature or fix a critical bug; he rolls up his sleeves and gets his hands dirty. A true hacker mindset, which, unfortunately, is not seen much these days."
"I can confidently predict that he has a bright future ahead, and feel grateful that at FIGLAB, we were able to provide him with the foundation to build that."
Direct LinkedIn recommendation from FIGLAB CEO · Verifiable public profile
Available for backend contracts, SaaS platform work, and AI workflow engineering. Based in Dhaka — working globally.