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Asad Abdul
Mid-level Full-Stack Developer specializing in AI-driven cloud-native applications
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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).
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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)
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