Shriya Bannikop

About

Full-stack engineer who built and owned an AI-assisted job-matching dashboard in Next.js App Router/TypeScript, keeping LLM logic server-side and improving performance via deduplication, caching/revalidation, and streaming (35% fewer duplicate LLM calls; 40% faster first render). Also has strong data/backend chops: designed Postgres models and optimized queries at million-record scale (1.8s to 120ms) and built durable AWS multi-region telemetry workflows with idempotency, retries, and monitoring.

Key Strengths

• Shipped full-stack Next.js (App Router) + TypeScript feature end-to-end and owned it post-launch
• Reduced duplicate LLM calls by 35% via centralized fetching, deduplication, caching/revalidation, and streaming with Suspense
• Improved time to first render by 40% through memoization and streaming LLM output
• Postgres query optimization at scale (1.8s to 120ms) using indexed joins and partial indexes validated with EXPLAIN ANALYZE
• Built durable AWS backend workflow for multi-region telemetry with retries (exponential backoff) and idempotent operations
• Made high-impact architecture decision to rewrite scaling algorithm with tests and progressive rollout, reducing incidents by 70%
• Balances speed and quality in high-growth environments using feature flags, testing, monitoring, and CI/CD

Experience

Education

Skills

Languages