AI Engineer

An AI-native software engineer. You've integrated AI deeply into how you build software—not as a novelty, but as a core part of your workflow. You ship faster because of it, with higher standards than ever before. You’ve developed a strong intuition for when to trust the model, when to push back, and how to steer it towards the results you want.

Grounded in engineering fundamentals. You understand that AI-assisted development still requires taste, judgment, and rigor. You care about code quality, testability, system design, and maintainability. You know that shipping fast means nothing if the code becomes unmaintainable or the system falls over in production.

Curious and constantly learning. The AI landscape changes weekly. You stay on top of new models, tools, and techniques—not out of hype, but because you're genuinely interested in finding better ways to build. You can separate signal from noise and identify which developments actually matter for shipping products.

Fluency with AI-assisted development. You've used tools like Cursor, Copilot, Claude, or similar to meaningfully accelerate your work. You understand prompting, context management, and how to get reliable results from LLMs in development workflows. You can teach others to be more effective with these tools.

Strong software engineering foundations. Production experience building and maintaining systems that matter. You write code that others can understand, test, and extend. You've debugged production issues, designed APIs, and made architectural decisions you had to live with.

Experience building AI-powered product features. You've shipped features that use LLMs, embeddings, or other AI capabilities directly—whether that's intelligent search, natural language interfaces, content generation, or agent-like functionality. You understand the unique challenges: latency, cost, reliability, evaluation, and graceful degradation when models behave unexpectedly.

Pragmatic judgment about when to use AI. Not every problem needs an LLM. You can identify where AI genuinely adds value versus where traditional software is simpler, cheaper, and more reliable. You make these tradeoffs thoughtfully.