AI Product Manager

Own the end-to-end experience. Design the dashboard and interface as a coherent whole, not a collection of features. Understand how each screen, workflow, and data point connects, and keep the system simple as it grows.

Design for real users under real load. Observe how team members work, find friction and repetitive effort, and design flows that streamline high-volume work. UX quality is a core deliverable, not a finishing touch.

Use AI to remove work, not create it. Identify where LLMs, RAG, and automation can take tasks off people’s plates — triage, summarization, flagging, routing, follow-ups — and design those capabilities so they feel invisible and trustworthy.

Build a unified view of the customer journey. Integrate conversations from customer Slack channels with our core applications and Google Sheets so the team sees one picture instead of many.

Make service proactive. Build systems that automatically flag and triage customer escalations before they become critical, and that help student success managers identify at-risk clients and trigger timely, automated follow-ups.

Prototype and verify quickly. Use Dify.AI to build LLM-powered prototypes, implement RAG, and iterate on prompts; use n8n to orchestrate automated workflows across third-party apps and APIs. Validate ideas with working prototypes before committing engineering time.

Lead AI product design. Prompt engineering, model selection and configuration, interaction design for AI features, and an evaluation framework that tells us whether an AI feature is actually working.

Run on data. Monitor product and AI-effect metrics, analyze user behavior, identify pain points, and drive continuous iteration.

Stay current. Track developments in AI tooling (Dify, n8n, Coze, and others), analyze competitors, and bring what’s useful back into our product.

Shape the roadmap. Contribute to short-term product planning and offer well-reasoned input on product strategy and technical direction.

2–5 years of product management experience, including 1–3 years designing AI-powered products.

Strong UI/UX judgment. You understand information architecture, interaction design, and how to design for people doing high-volume work. You can tell the difference between “has the feature” and “is pleasant to use,” and you care about the difference. Proficient with Figma, Axure, or similar.

Solid AI product fundamentals. Deep understanding of how LLM applications work; practical experience with prompt engineering and RAG; able to independently design, evaluate, and optimize an AI feature and balance technical feasibility against user experience.

Hands-on with AI tooling. Real-world experience with Dify.AI, n8n, or comparable platforms — you build, not just specify.

Technical fluency. Comfortable working closely with engineering and AI teams, understanding the principles and limitations of the technology, and helping get solutions shipped.

Systems thinking. You see how pieces connect and design for the whole, not the part in front of you.

Exceptional communication. Much of this role is talking to people, understanding their core needs, and finding a solution that works for everyone. Fluent English (spoken and written) and a talent for making complex things simple.

Independent drive. Disciplined, self-motivated, and able to deliver high-quality work in a remote environment without micromanagement. Strong sense of ownership.