Product Engineer
- Type
- Job
- Organization
- hyperexponential
- Location
- London (hybrid)
- Deadline
- Rolling or not stated
- Who can apply
- On-site in London (hybrid)
- Posted
- 6 November 2026
- Skills mentioned
- Rust, C++, Python
About this Opportunity
About hyperexponential (hx)At hyperexponential, we're building the AI-powered platform that enables the world's most critical decisions in a $7 trillion industry - which risks to take, and how to price them. These are the decisions that shape real-world outcomes: whether rockets successfully launch into space, autonomous vehicles make it to market, or communities recover after major storms.Until now, insurance has been making billion-dollar decisions using outdated tools. We're changing that. Our platform brings together data, AI, and human expertise to give insurers the fastest path from submission to decision - helping them move faster, act smarter, and take on more risk with confidence.Backed by a16z, Highland Europe, and Battery Ventures, we're scaling globally - already trusted by nearly 50 of the world's largest insurers, with zero churn and billions in premiums flowing through hx.What began as a single product in one market has rapidly evolved into a multi-product, multi-territory platform powering every stage of pricing and underwriting. AI is at the core of what we do - from building the world's first domain-specific AI peer programmer for insurance (think GitHub Copilot with a PhD in actuarial science) to shaping agentic workflows that reinvent how this industry operates.What makes hx different is the people who build it. Here, impact isn't tied to title or tenure; it's defined by the challenges you take on and the discipline you bring. Surrounded by peers who stretch you, you'll do the best, hardest work of your life in a company engineered to endure.If that sounds like you, join us in building what comes next.How we workWe're in the middle of a deliberate shift in how hx builds. Everyone in product development is a Builder, and the Product Engineer is the default unit of how we work.We organise around problems, not permanent teams. Small pods, usually of two to four Product Engineers, form around the highest-value problem, own it end-to-end from discovery through to running it in production, and re-form as priorities change. Pods sit inside value streams, each owning a customer outcome and led by a Stream Lead who decides which problems the stream takes on and holds the bar for what ships. Your growth sits elsewhere: a Career Mentor owns your development and progression, so you can move to where the most important problem is without your career following the org chart.We hire Product Engineers into hx, not into a fixed team, domain, or layer of the stack. You'll start in the stream where your strengths and our highest-value problems meet, and move as the problems move.Product Engineers are T-shaped: deep expertise in software engineering, plus enough product and design judgement to make routine calls yourself. An embedded PM or designer raises a pod's ceiling on the hardest problems, but is never a gate between you and the customer. This is also a deliberately AI-native role, and one of the areas where we're moving fastest.A pod of three owns its problem whole, which means going wherever it leads: front end, back end, data, or infrastructure. You don't need to be full-stack by trade, but you do need to be comfortable working outside your strongest layer.The Product Engineer role is the same at every level. What scales is the size of the problem you own, how expensive your decisions are to reverse, and how far your judgement travels beyond your pod. At Level 2, that looks like this: What you'll be doingTaking a customer problem from discovery to production inside a pod, getting close to customers yourself, framing the problem, and shipping in small increments guided by real customer signal rather than internal opinion.Directing AI agents to draft implementation, tests, and migrations, then reviewing, integrating, and hardening that work. You'll write intent precisely enough to brief both a teammate and an agent, and own correctness and maintainability regardless of how the first draft was produced.Designing and delivering robust production systems where correctness, performance, and resource efficiency matter, with the tests and observability that make complex behaviour safe to evolve.Working across the codebase wherever the problem leads, including areas your pod doesn't steward, with stewards looped in proportionate to the risk rather than handing work off and waiting.Moving between pods, problems, and streams as priorities change, ramping fast on unfamiliar domains and leaving what you built running well behind you.Taking full accountability for outcomes rather than just your code changes: raising risks early, and deciding rather than escalating.What you'll need to have doneBuilt and shipped production systems end-to-end, from design through rollout, monitoring, and iteration, in settings where correctness, performance, and resource efficiency mattered.Designed testing and observability that made complex behaviour understandable, debuggable, and safe to evolve.Worked effectively in a polyglot environment, choosing the right tool for the problem and picking up unfamiliar languages, domains, and codebases fast. Strong systems experience, for example in Rust, C/C++, or Python, is valued, and we'll upskill you where there are gaps.Shipped work outside your strongest layer of the stack when the problem needed it, picking up the front end, the data layer, or the infrastructure rather than waiting for someone else to.Used AI tools as a serious part of how you build, with the judgement to direct, review, and stand behind what they produce.Carried product and design judgement into your engineering work, shaping the solution rather than only implementing a spec and making sensible calls under ambiguity.Owned outcomes beyond your immediate task, taking decisions rather than escalating them.
Documents you may need
- Updated CV / Resume
- Cover Letter (tailored to this role)
How to apply
- Click the "Apply — via Arbeitnow" button to go to the source page.
- Read the full description and confirm you meet the requirements.
- Prepare your CV and cover letter tailored to this role.
- Submit your application through the official portal.
- Follow up within 1–2 weeks if you do not hear back.