We're looking for an AI Product Engineer to join the AI team and own how our product knowledge translates into reliable AI agent capabilities. This role sits at the intersection of product expertise and AI implementation. You won't write code or build ML models. Instead, you'll analyze agent interactions, create prompts and skills, improve documentation for AI consumption, label datasets, and write evaluations.
Think of this as a Knowledge and Content Manager for AI. You'll make sure our agents can accurately answer questions about us, guide users through workflows, and reduce support escalations.
Key Responsibilities:
Analyze AI inputs and outputs - Review agent conversations to identify gaps, hallucinations, and improvement opportunities
Create and maintain prompts and skills - Build reusable capabilities that encode our product logic and terminology
Improve documentation structure - Restructure docs so agents can cite accurate, step-by-step guidance
Label datasets and write evaluations - Measure agent quality across common questions and track improvements
Collaborate across teams - Work with Product, Docs, Support, and GTM to address real user pain points
Maintain the AI capability library - Keep prompts and skills organized with sendversioning and usage insights.
Requirements: Bachelor's degree in Computer Science, Technical Writing, or related field with 2+ years of professional experience
Daily use of AI assistants (Claude, ChatGPT) and coding agents (Cursor, GitHub Copilot) with basic prompt engineering skills
Strong technical writing ability focused on structure, clarity, and step-by-step guidance
Ability to quickly learn and explain complex technical concepts (APIs, infrastructure, developer workflows)
Basic coding skills (Python, JavaScript, or similar) to read and understand code examples.
Basic understanding of Git concepts and how code is managed in scale
Self-directed working style with strong attention to detail and analytical thinking.
This position is open to all candidates.