I build the AI
that does the QA.
Releases that ship faster and a QA budget that stops growing with the team. I build an orchestrated system of agents that runs the testing lifecycle and holds quality in production, release after release. From enterprise QA, to keeping AI products honest in production, to building the systems that test. The proof is not a title. It is what I have built.
From testing software to building what tests it.
A clear line through QA. Functional and manual testing first, then enterprise-grade test strategy, then the quality of AI products, then building the agent systems that run the testing themselves.
Enterprise QA
Test strategy and regression on a Big Four client’s audit and financial-data platform. Functional, exploratory, API.
Mobile QA
Owned iOS and Android release quality end to end, from requirement analysis to sign-off.
AI quality
QA lead on a production AI product. Built an AI-driven QA system from scratch.
Builder
Orchestrated agent systems in Claude architecture, with structural gates and cross-model second opinions.
Quality that costs less
and ships faster.
An orchestrated system of agents runs the testing lifecycle and holds quality in production, release after release. Not a bigger QA headcount: infrastructure that does the work, so releases go out faster and the testing budget stops scaling with the team. The agents write the tests and run them, triage defects, review code, watch production, and keep coverage in sync. AI-product testing, evaluation for non-deterministic output, hallucination, drift and prompt injection, is a specialty inside that, not the whole frame. The leverage is in the architecture, not the typing.
“Done” from an AI is not “correct.” A 200 OK is not the work landing. The check itself has to be checked, by a second independent pass.
- 01Multi-agent test pipelines. Specialist agents that handle non-deterministic output, not one prompt doing everything.
- 02Evaluation frameworks. Precision, recall, hallucination rate, drift. Quality criteria for stochastic output.
- 03Quality gates, prototype to production. The irreversible rules live in the structure, not the prompt. Described is not enforced.
- 04Cross-model second opinion. One model checks another. A degraded run raises instead of pretending to be healthy.
- 05Self-improving infrastructure. Corrections are captured and become rules, so the system does not drift back.
What I work with.
Hands-on QA on the manual side, plus the automation, CI, and frameworks I design and direct through AI. The methods that hold quality together, and the AI-quality layer where I go deepest.
Testing
Methods & practices
AI quality & automation
Stack
The proof, not the title.
One typed architecture over Claude Code, built solo for a production product, then carried into other domains. Open any system to see what it does, where the value is, and how it is built. The instance is replaceable. The method is the asset.
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Apr 2023
presentQA Engineer · AI ArchitectProduction AI product · remoteBuilt an AI-driven QA system from scratch that runs regression and API automation, designed the automation framework the team's Java suite runs on. Set release test strategy, owned quality gates and sign-offs, and mentored the QA team. -
Oct 2021
Jun 2025QA SpecialistBig Four client platform · audit & financial dataTest design, execution and review, defect reporting, root-cause and requirement analysis. Functional, exploratory, regression, cross-browser and API testing. -
Sep 2022
Jun 2023QA Engineer, mobile (part-time)iOS / AndroidOwned QA for iOS and Android releases end to end: requirement analysis, test design and release sign-off. Drove push-notification and back-office testing in direct work with developers, BAs and customers, with weekly QA reporting on release health.
Practice first,
theory reading it back.
On the Anthropic Solutions Architect track. I built the real systems first, the certification confirmed the method.
The person behind the systems.
I find the thought through working, not through buzzwords. Technical knowledge commoditizes. A sense of where a product is going does not. The systems I build are less about typing the code and more about deciding what to build, why, and how to keep it honest under pressure.
“I sit in the middle of the river, at anchor, and watch how it moves. Not drifting, not fighting the current. I move when I see where.”
Open to QA roles where AI is the job.
If you are bringing AI into your product and want quality that holds in production, I would like to hear about it. The fastest way to reach me is below.