Nitin W.
Engineering Leader | Event-Driven Architecture | LLM/AI Platform Development | AWS/Kubernetes | Ex-Founding Engineer
- Role
- Engineering Leader- Ml Ai Integrations and Cloud Operations at ApplyBoard
- Location
- Seattle, WA, US
- LinkedIn followers
- 500 followers
Experience
Engineering Leader- Ml Ai Integrations and Cloud Operations
Mar 2021 — Present
Architected the Application Automation platform (\"Road Runner\") that transformed a $10M annual cost center into a scalable, AI-powered system—reducing manual processing headcount by 80% while cutting application processing time from 6 days to under 30 minutes.The Challenge:When I joined, nearly operations staff manually processed student applications annually, creating significant delays and operational costs that threatened the company\'s ability to scale.What I Built:Designed and implemented \"Road Runner\"—an intelligent automation platform using event-driven architecture (SNS/SQS FIFO queues) and LLM-powered document processing to handle passports, transcripts, and English proficiency results with zero human intervention for qualifying applications.Key Achievements:→ Delivered ~$8M in annual cost savings through automation and operational consolidation→ Achieved 30% zero-touch application processing rate, with P95 latency under 5 minutes→ Architected idempotent, fault-tolerant systems using DynamoDB for deduplication and DLQ monitoring→ Engineered reusable async processing framework with generic retry/backoff, adopted across the engineering org→ Championed organizational shift from legacy RPA to modern LLM/agentic solutions for 10x efficiency gains→ Defined SRE governance including Error Budget Policies and firefighter rotations adopted org-wideEngineering Impact:→ Pioneered observability standards (distributed tracing, sequence diagram requirements) that became engineering org templates→ Mentored engineers on event-driven design patterns; coached team members through career transitions achieving first-cycle promotions→ Aligned Product, Operations, and AI/ML teams on multi-quarter technical roadmaps
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