I Anuj

About

Backend engineer with 1.7 years of experience plus prior founding experience who has already owned production systems end-to-end in an early-stage environment. Most notably, they rebuilt a failing ingestion pipeline into a stable SQS/Fargate architecture that improved success from 40% to 100%, boosted throughput 10x, and cut processing time by ~75%, while also shipping an LLM-powered fashion search workflow using Vertex AI and Elasticsearch.

Key Strengths

• End-to-end ownership of backend systems from design to production operations
• Re-architected ingestion pipeline from Lambda to SQS/Fargate
• Improved ingestion success rate from 40% to 100%
• Increased throughput from 10 to 100 requests (+900%)
• Reduced wall-clock processing latency by ~75%
• Strong reliability engineering for async systems
• CloudWatch-based autoscaling and queue-driven worker control
• Root-cause analysis of silent data loss in production
• LLM + search pipeline design for fashion assistant use case
• Prompt optimization that improved retrieval relevance from 0 to 6/10 results
• Balances reliability, scalability, latency, and developer velocity with clear tradeoff reasoning
• Works effectively in ambiguous early-stage environments

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