Cassidy Bridges

Inventoried 90+ AWS Lambda functions across Development, Test, and Production, mapping source repositories, shared layers, architectures, aliases, runtime versions, ownership, and invocation paths.

Converted a Python 3.9 runtime-upgrade mandate into a phased modernization plan evaluating Python 3.11, Python 3.12, and Amazon Linux compatibility, including a proposed 12-function pilot.

Incorporated lessons from a prior rollback affecting roughly 30 functions to define dependency risk tiers, release sequencing, QA scope, acceptance criteria, and promotion controls across development, test, and production.

Diagnosed production failures across distributed AWS integrations by tracing data through databases, API Gateway, Lambda functions, CloudWatch logs, source code, and external dependencies.

Aligned engineering, QA, delivery leadership, and dependent-system stakeholders around migration scope, validation requirements, rollout timing, and operational risk.

Led a performance overhaul that reduced sustained CPU peaks from 99% to 15% and lowered memory pressure, unlocking enterprise-scale workloads without new hardware.

Built "Bug Buddy," an AI-powered triage assistant that automated roughly 75% of manual classification and surfaced duplicate and regression patterns before engineering assignment.

Architected and led a multi-team refactor that retired 15,000+ lines of legacy code while moving the front end to TypeScript without pausing active feature work.

Rebuilt the front-end API layer to eliminate redundant requests and speed up rendering, then prototyped an LLM-assisted Redux-to-React Query migration that automated roughly 80% of conversion work.

Built the first white-labeled React dispensary menu, cutting manual inventory updates and custom branding work by 40+ hours per week.

Ran load testing, complex query analysis, and chaos engineering to keep commerce and reporting systems resilient through traffic reaching 4x normal volume.

Engineered pre-production and staging environments with feature branches and Kubernetes, eliminating QA environment queues and reducing test-cycle time by more than 80%.

Implemented redundant data storage, replication, and failover strategies to protect government reporting and customer workflows across multiple data centers.