Athul Thulasidasan

AI Inference Platform

Autoscaled Python backend services for AI workloads on AWS with Docker and Kubernetes, reducing inference workflow latency by about 50%.

OpenAPI Standardization

Standardized OpenAPI contracts across five business units and rolled them out behind feature flags, lowering integration failures by about 33%.

Observability Platform

Improved mean time to detection by about 40% through a Prometheus and Grafana based monitoring stack.

Vectorized Data Pipelines

Refactored legacy data flows into vectorized Pandas transformations, increasing large-scale processing throughput by about 2.5x.

TypeScript Migration

Migrated a production codebase from JavaScript to TypeScript with CI-enforced type checks, eliminating runtime regressions in core logic.

Performance Profiling

Used cProfile to identify hot paths and reduce CPU utilization by about 30% across the Node.js and Python stack.

Event Platform

Scaled backend services and REST APIs for a platform serving 50,000+ users with 99.99% uptime.

Payment Integrity

Developed a fault-tolerant payment flow with idempotency controls and Redis-backed audit logs, ensuring full data integrity.

Release Quality Gates

Integrated automated Postman testing and CI-driven quality gates, improving release stability to about 99% successful deployments.

API and Query Optimization

Refactored Flask REST services and optimized MySQL with compound indexes, query profiling, and multi-level caching for about 5x faster APIs and about 10x faster React page loads.

Mass Calculation Rewrite

Eliminated quadratic bottlenecks with memoization, batching, and precomputed Redis-backed lookups, cutting execution time by more than 55%.

CSV to MySQL Import Pipeline

Replaced Excel based imports with staged CSV ingestion, schema validation, transactional upserts, and failure alerts, reducing import time by about 67%.