At a Glance
- Tasks: Own end-to-end product features and deliver impactful solutions.
- Company: Join a fast-moving team revolutionising AI operations for retail and CPG enterprises.
- Benefits: Unlimited AI budget, autonomy, competitive salary, and equity options.
- Other info: Dynamic environment focused on learning, feedback, and rapid iteration.
- Why this job: Make a real impact with cutting-edge AI technology and solve genuine customer problems.
- Qualifications: Experience in shipping products, strong collaboration skills, and comfort with AI systems.
Who we are
Enterprise teams still copy data between systems all day. Work gets stuck in emails, legacy UIs, and handoffs. That chaos is costly, slow, and risky. We're a fast-moving team on a mission to end it for good. Traction is strong and we're solving real problems for real customers, but to win, we need exceptional talent. We stay humble, do the work, and let results speak.
What we are building
We're building the AI operations platform for retail and CPG enterprises—a horizontal platform where AI agents execute end-to-end work across UIs and APIs with governance built in. Where copilots stop, Duvo finishes the job. Business users specify the outcome; agents plan, act, request approvals on exceptions, and learn with every run. We start with a retail wedge (category management, supply chain, finance ops) where ROI is obvious, then expand to adjacent functions and sectors. Velocity is our moat: ship fast, iterate faster, compound learning.
The role
You will own end-to-end product features—from user-facing UI to API to data to deployment. You're the kind of engineer who connects technical choices to customer outcomes and ships with high velocity under ambiguity. Your unit of ownership: user-facing features and the systems behind them, delivered to production and measured against customer impact.
What we're looking for
- Shipping and ownership. You've repeatedly taken ambiguous requirements to production. You own the full stack of a feature (UI, API, data, deployment) and you don't wait for someone to tell you what to build next.
- Product judgment. You can define MVP scope, pick the right metric to move, and kill work that isn't delivering value. You think about what the user needs, not just what's technically interesting.
- AI comfort. You've worked alongside AI systems—at work or in side projects. You're comfortable building features that interact with LLM outputs (parsing agent responses, designing human-in-the-loop flows), but you won't be training models.
- Strong sense of product quality. You care about the details of how a feature looks and feels, not just whether it works. You notice when something is off and you fix it.
- Collaboration. You're low-ego and team-first. You give and receive direct and constructive feedback, align proactively with product and design, and unblock yourself and others.
- Judgment in a fast-moving environment. You'll often define your own scope based on customer problems surfaced through product feedback and competitive gaps — then ship it within a week.
You might also
- Have a strong sense for security and reliability in production systems.
- Have scalable, distributed-system instincts—you've designed and operated systems that scale.
- Have deep applied LLM experience—evaluation design, prompt engineering, safety controls, and cost optimization in production.
- Have experience designing interfaces for AI-assisted workflows — confidence signals, human-in-the-loop interactions.
This is not for you if
- You need significant hand-holding or aren't energized by figuring things out yourself.
- You primarily want to work on infrastructure (see our SRE and AI Platform Engineer roles).
Our tech stack
TypeScript-first: Next.js, React, Tailwind, Fastify, Kysely (PostgreSQL), ZodGCPLatest AI primitives. You don't need to know all of these, but you should be excited to learn them quickly.
How we work
These Are Real Tradeoffs We've Made, Not Aspirations
- Initiative-driven. We organise around customer problems, not org charts. Problems surface through product feedback, competitive analysis, and direct customer conversations — then we prioritise, build, and ship weekly.
- Customer-obsessed. We solve real problems, not hypothetical ones. Features that don't move customer metrics get cut.
- Iterative by default. We ship small, learn fast, and never get attached to yesterday's code. This means things break sometimes — we fix forward.
- AI-first leverage. We use AI to move faster and focus human time where it matters most. If a tool can do it, a person shouldn't.
- Direct feedback. We give each other actionable feedback immediately. This can feel uncomfortable — we think that's worth it.
- Autonomy with accountability. We trust people to make decisions and hold them to outcomes, not process.
What we offer
- Unlimited AI budget. We don't just allow AI tools — we strongly encourage them. Want to try a new tool? Buy it. Want to automate part of your workflow? Do it.
- Autonomy to do your best work. Want to meet someone to learn from? Set it up. Want a mentor? Go get one. Want to fly out to talk to an important customer? Just ask.
- A real AI product with real customers. You're not building demos or internal tools. Enterprise customers use what you ship, and their feedback drives what you build next.
- A sharp, motivated team that values ownership and candor.
Compensation
250.000,- CZK / month with a meaningful equity component. You can trade salary for additional equity if you prefer more upside.
How we hire
We Respect Your Time And Aim To Move Fast
- Hiring manager screen (30 min). We'll talk about you, how you think and whether there's mutual fit.
- Remote task (async, time-boxed, ~1 hour). Build a small product end-to-end. Not LeetCode.
- Technical interview (Prague, ~1 hour). Meet the team. We'll go deeper on your experience, system design, product thinking, and collaboration. No trick questions — we want to see how you think and build.
- On-site trial day (2 days). Ship something small to production with us and see how we work together. Fully compensated.
AI Product Engineer - End-to-End Ownership in Harrow employer: duvo.ai
At Duvo, we pride ourselves on being an exceptional employer that fosters a culture of autonomy, innovation, and collaboration. Our team is driven by a shared mission to solve real problems for our enterprise customers, offering unlimited AI budgets and opportunities for personal growth in a fast-paced environment. With a focus on meaningful work and direct feedback, we empower our employees to take ownership of their projects and make a tangible impact in the retail and CPG sectors.
StudySmarter Expert Advice🤫
We think this is how you could land AI Product Engineer - End-to-End Ownership in Harrow
✨Tip Number 1
Get your networking game on! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have a lead on that perfect AI Product Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those involving AI systems. This gives you a chance to demonstrate your end-to-end ownership and product judgement in action.
✨Tip Number 3
Prepare for interviews by practising common questions related to product engineering and AI. Think about how you can articulate your experience with shipping features and collaborating with teams. We want to see your thought process!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our mission to solve real problems for real customers.
We think you need these skills to ace AI Product Engineer - End-to-End Ownership in Harrow
Some tips for your application 🫡
Show Your Ownership:When you're writing your application, make sure to highlight any projects where you've taken the lead from start to finish. We love seeing candidates who own their work and can connect their technical choices to real customer outcomes.
Be Customer-Obsessed:In your written application, focus on how you've solved real problems for users in the past. We want to know about the metrics you’ve impacted and how you’ve iterated based on feedback. Show us that you think about what users need!
Demonstrate Your AI Comfort:If you've worked with AI systems, whether in a job or side projects, let us know! Share specific examples of how you've built features that interact with AI outputs. This will show us you're ready to dive into our AI-first environment.
Keep It Clear and Concise:While we appreciate detail, clarity is key. Make sure your application is easy to read and gets straight to the point. We want to see your skills shine without wading through unnecessary fluff. And remember, apply through our website!
How to prepare for a job interview at duvo.ai
✨Understand the Product and Its Users
Before your interview, dive deep into the product and its target users. Familiarise yourself with how the AI operations platform works and think about the user experience. This will help you articulate how your skills can directly impact customer outcomes.
✨Showcase Your Ownership Experience
Be ready to discuss specific examples where you've taken ambiguous requirements and turned them into successful products. Highlight your end-to-end ownership of features, from UI to deployment, and how you measured their success against customer metrics.
✨Demonstrate Your AI Comfort
Since the role involves working with AI systems, share any relevant experiences you have with AI projects. Talk about how you've interacted with LLM outputs or designed workflows that incorporate human-in-the-loop processes. This will show your comfort level and readiness to tackle AI-related challenges.
✨Emphasise Collaboration and Feedback
Prepare to discuss how you work within a team and handle feedback. Share examples of how you've given and received constructive criticism, and how you align with product and design teams. This will demonstrate your low-ego, team-first mentality, which is crucial for success in this fast-moving environment.