Leading platform architecture for an AI data-classification product
Tech-led the platform architecture for an AI-driven data-discovery product serving enterprises across LATAM.
The Anvil
Kriptos helps enterprises discover and classify sensitive data across sprawling content estates. As the product matured, the platform needed to scale to larger ingestion volumes — and logging and tracing costs ballooned with it. That growth piled on tech debt the way it does at fast-scaling startups.
The Strike
As technical lead and solutions architect, I shaped tech-debt visibility and strategy, and led the logging initiative using only open-source solutions (AWS was ruled out on cost). Concrete moves: laid out a phased migration for logging and built the foundation for it; established CI/CD discipline; and produced artifacts that made tech debt visible and actionable. Worked with a team of 5 across multiple squads.
The Edge
I delivered a phased logging strategy the team could roll out incrementally; the tech-debt analysis was adopted across all squads and pods, breaking the work into manageable slices the team could tackle alongside delivery.
More Forged Works
#004 An observable QA pipeline: .NET, Playwright, GitHub Actions, Datadog CI Visibility
Designed and built the end-to-end QA automation pipeline — Playwright on .NET, orchestrated through GitHub Actions, observed live via Datadog CI Visibility — for a confidential enterprise client.
#002 Modernizing CI/CD for a legacy ASP.NET platform
Increased velocity and visibility for CI/CD.
#003 A polyglot platform with embedded ML at PPM
Worked across the whole stack — Go, Node, and PHP behind the API line, React/Redux up front, scikit-learn powering the analytics.