Hiring pipeline for AI-native engineers, run as a product deployment image

INTERNAL / EVALUATION SYSTEM

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Hiring pipeline for AI-native engineers, run as a product

Engagement

Roles-and-applications pipeline

Capabilities

Structured evaluation, real-work scoring, and AI-enabled interviews

Context

Our own problem: finding engineers who can own outcomes, not tickets.

Evaluation moved from impression to evidence, and the same infrastructure now supports client hiring conversations.

The problem

Resumes are a weak signal for this, and "AI-heavy" resumes are now trivially easy to generate.

What we built

A roles-and-applications pipeline wired to our own operating stack, plus a structured evaluation approach that scores real work instead of claims — including interviews where candidates are expected to use AI.

What changed

Evaluation moved from impression to evidence, and the same infrastructure now supports client hiring conversations.

What we'd do differently

Every internal system we build is a rehearsal for a client deployment. This one became a reusable pattern for evaluating any judgment-heavy process.

The next deployment

Bring us a workflow, not an RFP.

We'll tell you honestly whether AI should touch it.

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