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Minh Huynh
Junior AI/ML Engineer specializing in LLM systems and personalization
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Backend engineer who built and scaled AmazonProAI, a multi-tenant SaaS platform for Amazon sellers, using a modular Django/DRF monolith with strict seller-level isolation and security controls. Led a controlled SQLite-to-PostgreSQL migration and hardened bulk Excel ingestion with idempotency and data integrity constraints to prevent duplicate metrics and noisy alerts while keeping the system ready for future service extraction.
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Key Strengths
- Designed and evolved a multi-tenant SaaS backend with strong tenant data isolation
- Pragmatic architecture: modular monolith with clear domain boundaries and seams for future service extraction
- Security-first API design (JWT/OIDC, RBAC/ABAC, centralized authorization enforcement)
- Led SQLite-to-PostgreSQL migration with staged dry-runs, verification, and rollback planning
- Reliability engineering: idempotent ingestion via unique constraints/upserts/transactions to prevent duplicate metrics and alert noise
- Performance/scalability fundamentals: indexing, pagination/filtering, avoiding N+1 queries, vertical scaling + multi-worker deployment
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