Less telling.
More working proof.

The API was repeatedly restarted, while each report pointed to a different symptom—CORS, session expiry, or incorrect state—so the actual cause remained unknown.

I initiated APM adoption and correlated traces, logs, and database evidence. We isolated a write-connection leak, audited nine similar patterns, and redesigned health checks and pool limits.

The incident stopped recurring and evidence-driven analysis became a documented team practice. The team achieved 209% of its cost KPI while progressing three new products.

When every AI experiment owns separate auth, deployment, and data, little remains for the next one. A repeatable service foundation mattered more than another model call.

I built RS256/JWKS auth, an Agent API with worker pools and queues, both PostgreSQL FTS and pgvector RAG, and a fixed ARM64 delivery path with Terraform and GitHub Actions.

As of July 2026, the platform connected 12 repositories and 490 commits. After five product validation cycles, data and files were preserved in architecture-independent backups.

Policy and business rules changed often, while failures in overnight batches or agency integrations could affect front-line service the next morning.

In a Java, Spring, and Oracle environment, I structured business rules into batches and procedures, designed exception and retry paths, and worked across new systems and external APIs.

The system reliably processed over 100,000 eligibility records a day. I contributed to an in-house operating model that reduced vendor dependence and received an institutional commendation.