At a Glance
- Tasks: Design and build innovative front-end experiences for AI-driven insurance solutions.
- Company: Join a forward-thinking company revolutionising specialty insurance with AI.
- Benefits: Enjoy meaningful autonomy, remote work, and the chance to make real impact.
- Other info: Collaborate with a global team and enjoy short feedback loops.
- Why this job: Shape the future of insurance by creating user-friendly, data-rich interfaces.
- Qualifications: Experience in product design and specialty insurance is essential.
The predicted salary is between 56700 - 69300 £ per year.
This role is for someone who helps shape what’s worth building, designs it by building, and owns the result in production. You explore and prototype like a designer, then carry the strong ideas all the way to a shipped front-end, the exploration and the building as one craft rather than two stages with a handoff between them.
When the same person designs and builds, there’s no spec to hand off and no rebuild cycle, so the work moves faster and the original intent carries straight through. You work in Product & Technology squads built for the AI era, alongside software engineers who own the systems beneath the experience: they’re accountable for whether it runs, you’re accountable for what it is. This is not a designer who occasionally prototypes or a front-end engineer who takes tickets.
Most of what gets called “AI in product” today is a button bolted onto an unchanged screen. We’re building the opposite: experiences where the agent does the work and the human reviews, corrects, and authorizes it. Knowing the difference, and being able to design and ship it, is the judgment we’re hiring for.
Where You’ll Have Impact
You’ll join Agentic MGA, the squad that powers risk selection before a policy is bound. The squad gives underwriters and members self-serve pre-bind analytics, pricing and appetite insight, and intelligence that learns continuously from submissions, bind outcomes, and claims performance.
The surfaces you design carry real underwriting decisions: what to quote, what to decline, what sits inside appetite and what does not. The system learns from what happens after those decisions, so the experience has to make the reasoning legible, not just deliver an answer. Some of this is making dense insurance data clear and usable under time pressure. Some of it is rethinking a workflow entirely now that an agent can carry the load. You will own these from shaping the problem through to the production front-end, working with software engineers on the systems underneath.
What You’ll Do
- Explore and prototype to find the right answer. Real design happens here: trying directions, putting things in front of people, following the good ideas and throwing out the rest. Most of what you make is for learning, not shipping, and that’s the point. Production is where the right answer lands, not where it starts.
- Carry features from design through to production front-end. The design decision and the code are the same job, in the same hands, so the work keeps its fidelity instead of being lost in a handoff.
- Help frame what’s worth building. Talk to underwriters and members, test whether the problem is real, and shape scope alongside your squad rather than waiting for a finished spec.
- Build the supervisory surfaces of an agent-native platform: a submission triage queue an underwriter trusts at a glance, a confidence and citation pattern they can act on, an appetite or pricing signal that shows its reasoning.
- Use AI tools across the full loop (research, design, prototype, build, test, iterate) as the default way you work, not an occasional accelerator.
- Own the invisible craft that separates polished from pretty: performance, accessibility, cross-device behaviour, and the responsiveness that makes an interface feel fast.
- Build with and contribute to our AI-native design system: the patterns, rules, and decision logic that let people, AI, and engineers create coherent, on-brand experiences from a shared foundation.
- Ship early, learn from users and production, and iterate continuously, applying real judgment to AI-generated output rather than trusting it.
What We’re Looking For
- A builder who designs and ships front-end to production. You’ve owned a problem, made the call on what the experience should be, and shipped it yourself.
- Specialty insurance experience, on the pre-bind side. This one is a requirement, not a preference. You understand what an underwriter is doing when they assess a submission, what appetite means in practice, how an MGA differs from a carrier, and why bind rate and loss performance are the numbers that matter. You’ve designed for these users before, and you can tell when a workflow is wrong on the business logic and not just the interaction.
- You set direction without a brief. You take an ambiguous problem area, decide what matters, and get it moving. You are the design judgment on your squad and comfortable being the person accountable for whether what ships is good.
- Strong design judgment and taste. In a world where AI produces competent interfaces instantly, the ability to tell good from merely functional, and to push work past the default, is the scarce skill.
- Product instinct. You can tell what’s worth building, cut scope without being told to, and validate with real users rather than waiting for certainty.
- Comfortable building and shipping production-quality front-end in a modern web codebase, using AI tooling at every stage. You know AI’s failure modes, can tell when output looks right but isn’t, and own the quality rather than trusting it. We care that you can ship and know when it’s right, not which framework you came up on.
- A genuine interest in using AI not just to produce screens faster, but to rethink what designing a product even is when the agent does the work and the human supervises.
- The ability to design data-rich, high-stakes interfaces for demanding professionals who are making consequential decisions quickly.
- Depth and quality of your experience matter more than years, and there is no single right background on the build side. Strong candidates come from design, from engineering, and from places in between. The insurance experience is the one thing we are firm on. This is not a role for someone early in their career.
Why Join Accelerant?
- Real impact: you’re building the experiences that change how specialty insurance operates, for customers inside and outside Accelerant.
- Real ownership: short feedback loops, meaningful autonomy, and builders trusted to make consequential decisions and ship them.
- AI-native by default: we use AI seriously, both in how we build and in what we deliver to customers, and this role is at the center of that.
- One craft, not two handed off: design and engineering in the same hands, on the same squad, shipping the same work.
- A remote-first squad of talented people working together across the globe.
Product Design Engineer employer: Accelerant
At Accelerant, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to excel in their roles. As a Lead ML Platform Engineer, you will have access to cutting-edge technology and the opportunity for professional growth while working alongside talented data scientists and engineers in a dynamic environment. Our commitment to employee development and a focus on impactful projects makes us an exceptional employer for those seeking meaningful and rewarding careers in AI and machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Product Design Engineer
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We think you need these skills to ace Product Design Engineer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Accelerant.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Accelerant and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Accelerant
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Accelerant uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.