> cat ai_skills.txt

AI & LLM Engineering Skills

As LLMs become part of real products, they need the same rigor as any other backend โ€” verified quality, safety and cost, not just a nice-looking demo. Here's what that looks like in practice.

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Hallucination & Groundedness Testing

Building automated checks that verify an AI's answer is actually grounded in the facts it was given โ€” not invented, no matter how confident it sounds.

โœ“ Proven in AI & LLM Testing Framework
๐Ÿ›ก๏ธ

Prompt Injection & Guardrail Testing

Testing that a model safely refuses harmful or manipulative prompts โ€” while making sure it doesn't over-refuse and block legitimate questions too.

โœ“ Proven in AI & LLM Testing Framework
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Structured Output Validation

Verifying AI-generated JSON actually parses and matches an exact expected schema โ€” critical the moment an LLM's output feeds into other code.

โœ“ Proven in AI & LLM Testing Framework
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Latency & Token-Cost Budgeting

Asserting AI responses stay within acceptable speed and cost limits โ€” treating an LLM call like any other API that has a performance budget.

โœ“ Proven in AI & LLM Testing Framework
๐Ÿงช

Test Automation for AI Systems

Building PyTest frameworks around a deterministic mock LLM client, so AI behavior can be tested reliably and cheaply in CI โ€” no flaky outputs, no per-run API cost.

โœ“ Proven in AI & LLM Testing Framework
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Prompt Engineering & Test Data Design

Designing prompt sets as structured, reusable test data kept separate from test logic โ€” covering both expected-good and deliberately adversarial model behavior.

โœ“ Proven in AI & LLM Testing Framework
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Autonomous Agent Skill Design

Writing structured operating guidelines that let an AI coding agent work autonomously within a defined domain โ€” debugging, refactoring and validating its own changes safely, with clear scope and boundaries instead of a prompt for every step.

โœ“ Applied in real autonomous engineering workflows

See it in code

These aren't abstract concepts โ€” every skill above is backed by a real, working test suite with 12 passing tests and a CI pipeline that runs it on every push.