Staff AI Designer

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences.

Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams.

Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers.

Role Overview

We’re looking for a Staff AI Product Designer to shape what our AI does, how it behaves, and how it fits into real user workflows.

This role sits at the intersection of product, design, and machine learning—turning emerging capabilities into reliable, high-quality user experiences. You’ll design systems: behaviors, decisions, orchestration, and end-to-end experiences powered by AI.

This is not a traditional product design role. You’ll go beyond interface design to define how AI systems behave, operate, and deliver value in the real world—similar to emerging “AI Model Designer” roles, but more deeply embedded in product.

What You’ll Do

1. Define AI capabilities (the “what and why”)

Identify and pattern match high-value opportunities for AI across the product

Define what AI should do—and just as importantly, what it should not do, making hard or unpopular calls when needed

Set clear boundaries for autonomy vs human control

2. Design AI behavior, orchestration, and system logic

Architect AI-driven workflows and agentic systems that operate across real-world scenarios and over time, including multi-step and agent-to-agent interactions

Establish decision frameworks: when systems should act, ask, escalate, or defer

Design for uncertainty, failures, and edge cases as core system behavior

Develop and apply design principles and heuristics to shape how AI systems behave and make decisions

Ensure systems remain coherent and predictable, even as complexity scales

3. Shape human + AI workflows and end-to-end experience

Design experiences for users who are increasingly managing AI systems and agents

Design how AI integrates into real user workflows, not just isolated interactions

Define the role of the human in the loop: where users guide, review, or override

Ensure users can understand, trust, and recover from system failures

Partner with product designers to continuously shape and adapt the product experience as underlying systems evolve

4. Define quality, evaluation, and reliability

Define what “good” looks like (e.g. trust, accuracy, effort reduction, and whether outputs are structured and usable in context)

Design evaluation scenarios and feedback loops

Analyze outputs to identify failure modes and system weaknesses

Design for reliability at the system level, preventing agentic breakdowns

How You’ll Work

Shape direction from the earliest stages of zero-to-one problems

Influence across teams without formal authority

Operate in a highly autonomous, fast-moving environment with evolving constraints

Lead ambiguous, in-flight work—making calls on when to adapt the product vs. push on system improvements as things evolve

Act as a bridge between AI research, technical capabilities, and user needs

Collaborate deeply with ML scientists, PMs, and product designers

Prototype and run focused experiments that isolate variables and generate clear insights

Stay close to system behavior by regularly reviewing outputs and raising