The Role

• Own AI product initiatives end-to-end — from problem discovery and technical approach to launch, iteration, and long-term quality
• Talk to customers constantly, turning messy qualitative feedback into clear product direction, priorities, and tradeoffs
• Define and measure quality for AI systems, establishing what “good enough” means and how to improve it over time
• Partner deeply with engineering and design on AI-first workflows, system constraints, and user experience
• Use data to guide decisions, combining metrics, experiments, and qualitative insight to iterate under ambiguity
• Create clarity and momentum, turning vague problems into concrete plans, shipped features, and learning loops
• Make strong product judgments, balancing UX, technical feasibility, AI limitations, cost, and business impact

What You’ll Do

• Customer-Centric Product Thinking: You have strong instincts for user problems and back them up with real customer exposure. You don’t build features just because they were requested — you synthesize, prioritize, and push back when needed.
• Technical Fluency with AI Systems: You can credibly partner with engineers on AI-driven products. You understand concepts like pipelines, latency, cost tradeoffs, evaluation, and failure modes — and you’ve shipped and iterated on AI features before.
• Strong Product Judgment & Taste: You have a point of view on quality. You can look at an AI-generated output and quickly identify what’s wrong, what matters most to users, and what’s worth fixing now versus later.
• Data-Driven Decision Making: You frame problems with hypotheses and success metrics, use data to validate (or invalidate) assumptions, and avoid hiding behind “we didn’t have enough data.”
• Execution & Organization: You turn ambiguity into progress. You communicate clearly in writing, manage priorities well, and ship without excessive process or chaos.
• Strategic Perspective: You connect day-to-day product decisions to broader business goals and long-term leverage, balancing quick wins with durable quality improvements.

Nice to Have

• Experience shipping generative visual AI products where output quality is variable or probabilistic
• Familiarity with brand consistency challenges in products (guidelines, compliance, style systems)
• Experience working closely with go-to-market teams on launches, positioning, or customer education

Why Arcade

• High ownership: you’ll directly shape how AI shows up in the product
• Real customer impact: your work will be used daily by product, sales, and marketing teams
• Small, senior team: tight collaboration with engineering, design, and leadership
• Meaningful AI problems: quality, trust, evaluation, and UX, not just prompt tuning. If you’re excited about building AI-powered products that customers actually trust and use, we’d love to talk.