Asad Abdul

About

Full-stack engineer with healthcare/ops analytics experience at PatientXpress, shipping a real-time operational dashboard end-to-end (React/TypeScript + Node/Postgres on AWS) that cut manual reporting by 50%. Strong in performance and reliability work—pagination/caching, Postgres indexing/partitioning, Terraform-based AWS provisioning, CI/CD with GitHub Actions, and production incident response with improved monitoring (CloudWatch/Prometheus).

Experience

Education

Key Strengths

• Shipped end-to-end real-time operational dashboard to production (design → API → deployment)
• Reduced manual reporting time by 50% via analytics dashboard
• Performance optimization for large datasets (pagination, caching, PostgreSQL query/index tuning)
• Production AWS operations and incident response (identified DB bottleneck, scaled RDS, optimized queries, added autoscaling/monitoring)
• Infrastructure automation with Terraform + Docker and CI/CD with GitHub Actions
• API design for AI-driven search (REST, versioning, JWT/OAuth2, consistent error handling)
• Built polished React + TypeScript UI with resilient data fetching (React Query caching/retries, loading/empty states, error boundaries)
• Owned and shipped end-to-end full-stack AI support feature (React/Next.js + Node + Python RAG) through production deployment on AWS
• Measured post-release impact: 30% reduction in support query response time; improved user satisfaction via surveys
• Strong API design under mixed workloads (lightweight sync endpoints vs async AI-heavy endpoints) with strict contracts and pagination
• Performance optimization across stack: PostgreSQL query tuning/indexing, Redis caching strategy, reduced repeated vector lookups
• Pragmatic caching decisions to avoid stale/incorrect AI outputs (cache deterministic metadata/permissions; avoid caching AI responses)
• Built reliable data pipelines/integrations with idempotency, retries/backoff, DLQs, backfills, and monitoring/alerting
• Designed maintainable modular architecture and standardized typed components/validation/error-handling patterns to improve onboarding and velocity
• Operated production systems with AWS reliability/observability practices (CloudWatch dashboards/alarms, autoscaling, rolling deploys, env separation)