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Enterprise work still moves by hand: copy-pasting between spreadsheets, endless email threads, and clunky legacy UIs. We started Duvo to end that for good.
We've already earned the trust of a range of customers, and our agents are helping them automate business-critical processes. We are growing fast, but to win from here we need exceptional people; that's where you come in.
We're building the AI operations platform for large enterprises, currently focused on retail and consumer packaged goods customers. In Duvo, customers build AI agents that execute work wherever it needs to get done—SAP, spreadsheets, supplier portals, email, APIs, you name it. Duvo is heavy on browser and computer use.
In Duvo, business users specify the outcome; agents plan, act, request approvals on exceptions, and learn with every run. To help customers understand what to automate, we also help them map their processes by digesting interviews and internal documentation, which gets our foot in the door. We start with automating the parts of companies that we know best (category management, supply chain, finance ops) where we can show value fast, then expand to adjacent functions and sectors.
Velocity is our moat: ship fast, iterate faster, compound learning.
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.
These are non-negotiables. The things we'll specifically evaluate you on:
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.
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.
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).
We're looking for people within two hours of Prague (CET), so the team overlaps for most of the working day.
GCP (Cloud Run, GKE, GCS)
Terraform, Docker
Datadog
TypeScript and Python services (you'll read and occasionally modify application code, but deep language expertise isn't required)
Postgres, Redis
These are real tradeoffs we've made, not aspirations:
Initiative-driven. We organize around customer problems, not org charts. Problems surface through product feedback, competitive analysis, and direct customer conversations — then we prioritize, 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.
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.
We respect your time and aim to move fast:
Discovery call (online, 30 min). We'll talk about you, how you think and whether there's mutual fit.
Technical interview (online, ~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 (1 day). Ship something small to production with us and see how we work together. Compensated.
Compensation Range: €110K - €220K
London, United Kingdom · Remote
Full Time
€110,000.00/yr - €220,000.00/yr
Posted September 28, 2026
English