Hi, I'm Jay Chothiyawala
AI Engineer and Full-Stack Developer building scalable, production-ready systems end-to-end.
Work Experience
Full Stack Developer Intern
- Built an interactive geospatial skill map covering 10 industry verticals using Leaflet.js and Google Places Autocomplete.
- Aggregated thousands of profiles into PIN-code clusters for performant rendering and privacy-preserving coordinate jitter (1.5km), backed by 3 FastAPI aggregation endpoints and a Power BI-styled dashboard.
- Designed a crew rostering system serving hundreds of workers across dozens of client sites: a 3-tier greedy scheduling engine producing near-optimal assignments in milliseconds.
- Developed a drag-and-drop scheduling board and an automated no-show sweep every 30 minutes with a 30-minute grace window.
- Developed secure, anti-fraud attendance APIs leveraging biometric face matching and local Haversine-distance geofencing to guarantee employees were within 10 meters of their assigned office upon check-in.
- Built cross-system identity bridging and service-to-service JWT authentication linking two independently deployed databases (PostgreSQL and MySQL).
Freelance Developer
- Delivered multiple freelance projects, owning end-to-end architecture, development, deployment, and post-launch support for independent clients.
- Designed scalable backend services using Java, Spring Boot, PostgreSQL, MongoDB, Redis, and Kafka.
- Containerized applications using Docker and deployed scalable workloads to Kubernetes across AWS and Azure, with CI/CD via GitHub Actions.
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I am an AI Engineer and Full-Stack Developer with a deep interest in building scalable, reliable, and intelligent web applications. My focus spans robust backend architectures with Java and Spring Boot to high-performance AI microservices utilizing Python, FastAPI, and LangChain. I also enjoy creating clean, responsive frontends with React and Next.js to turn complex system designs into seamless products.
I am passionate about learning by shipping real software. I enjoy tackling challenges ranging from database failover and distributed system design to deploying containerized workloads via Docker and Kubernetes on cloud platforms like AWS and Azure. My ultimate goal is to grow as an engineer who can own end-to-end solutions, bridging the gap between cutting-edge AI capabilities and resilient backend infrastructure.