Software Engineer, Applied AI

Key Requirements

• 2+ years of experience building production software systems, with exposure to AI or ML-driven features.
• Working understanding of modern AI concepts: LLMs, embeddings, retrieval systems, and at least the basics of agentic design patterns.
• Solid engineering fundamentals (Python and/or TypeScript/Node.js) and experience contributing to backend services in production.
• Ability to implement well-scoped solutions from clear technical direction, and to flag when scope or approach needs discussion.
• Thinks about whether an agent or model-driven approach could fit a problem before defaulting to traditional code.
• Genuine curiosity about how AI systems work, not just as a user, but as someone who wants to understand and improve them.
• Growth mindset: you're honest about what you don't know and proactive about closing the gap.
• Comfort with day-to-day ambiguity: you can make progress even when the full picture isn't clear.
• Pragmatic instincts: you'd rather ship something good than stall waiting for something perfect.
• Clear communicator who asks good questions and knows when to seek input.

Nice-to-Have

• Has used AI coding tools (Cursor, Claude Code, Copilot, etc.) as a meaningful part of a real project and can speak to what that changed.
• Has built a small agentic workflow, LLM-powered tool, or AI-assisted automation, even as a side project or exploration.
• Familiar with evaluation and testing approaches for AI outputs (prompt testing, output comparison, basic regression).
• Has experimented with frameworks or tools in the AI ecosystem: LangChain, LlamaIndex, LangGraph, Anthropic tool use, OpenAI function calling, or similar.
• Has replaced something they did manually with an AI-driven workflow and can describe what they learned.
• Reads about AI developments with genuine interest and forms opinions about them.