Staff AI Designer

Dublin, Ireland

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 the bar on quality

What We're Looking For

Strong product judgment—you consistently make high-quality calls on what to build and why

Ability to influence without authority

Experience working on zero-to-one products and comfort operating through ambiguity and rapid change

Deep understanding of LLMs and their limitations, along with a grounding in traditional ML approaches and when to use them instead

Experience defining design principles, heuristics, or evaluation criteria for AI systems

High standards for quality, with a track record of identifying where AI systems break down in real-world use

A scientific mindset—you can design experiments that isolate variables and produce meaningful insights

Systems thinker: you're happier designing behaviors and flows than polishing interfaces

We're open to non-traditional backgrounds (e.g. product managers, engineers, or others) if you have strong product sense and a track record of representing user needs in technical systems

What This Role Is Not

You will not be training models or building ML infrastructure

You will not be responsible for backend architecture or performance optimization

You will only occasionally design UI—this is not the focus of the role

You will influence all of these—but your primary responsibility is defining what should be built, how it should behave, and how it performs in the real world.

Why This Role Is Compelling

You'll join a mature AI discipline operating at the frontier. Fin already has an established AI Design team and strong cross-functional understanding of this role, so you can focus on building rather than justifying your value.

You won't be "adding AI to a product." The quality of our AI is the quality of our product. This is a technical, hands-on role where you have the satisfaction of working with tight feedback loops.

You'll shape product direction, not just execution. You'll operate upstream in a high-autonomy environment with real ownership over outcomes.

Benefits

We are a well treated bunch, with awesome benefits! If there's something important to you that's not on this list, talk to us!

Competitive salary and equity in a fast-growing start-up

We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen

Regular compensation reviews - we reward great work!

Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated.

Pension scheme & match up to 4%

Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents

Flexible paid time off policy

Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones

If you're cycling, we've got you covered on the Cycle-to-Work Scheme. With secure bike storage too

MacBooks are our standard, but we also offer Windows for certain roles when needed.

#LI-Hybrid Policies

Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values .

Fin values diversity and is committed to a policy of Equal Employment Opportunity. Fin will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.

Strong product judgment—you consistently make high-quality calls on what to build and why

Ability to influence without authority

Experience working on zero-to-one products and comfort operating through ambiguity and rapid change

Deep understanding of LLMs and their limitations, along with a grounding in traditional ML approaches and when to use them instead

Experience defining design principles, heuristics, or evaluation criteria for AI systems

High standards for quality, with a track record of identifying where AI systems break down in real-world use

A scientific mindset—you can design experiments that isolate variables and produce meaningful insights

Systems thinker: you're happier designing behaviors and flows than polishing interfaces

We're open to non-traditional backgrounds (e.g. product managers, engineers, or others) if you have strong product sense and a track record of representing user needs in technical systems

What This Role Is Not

You will not be training models or building ML infrastructure

You will not be responsible for backend architecture or performance optimization

You will only occasionally design UI—this is not the focus of the role

You will influence all of these—but your primary responsibility is defining what should be built, how it should behave, and how it performs in the real world.

Why This Role Is Compelling

You'll join a mature AI discipline operating at the frontier. Fin already has an established AI Design team and strong cross-functional understanding of this role, so you can focus on building rather than justifying your value.

You won't be "adding AI to a product." The quality of our AI is the quality of our product. This is a technical, hands-on role where you have the satisfaction of working with tight feedback loops.

You'll shape product direction, not just execution. You'll operate upstream in a high-autonomy environment with real ownership over outcomes.

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