
Duvo · London
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 ri...
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.
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.
You will own the technical direction and delivery of an initiative. You're an excellent product engineer who ships code alongside
your team — expect to spend 50–60% of your time in code.
This is not a management role. You write production code, review PRs, make architecture calls, and set the engineering standard
your team rallies around. Your leadership is rooted in technical credibility and active presence in the codebase.
You run 1:1s with engineers on your initiative — focused on the work: delivery, unblocking, and direction. You're involved in
hiring because you define how your initiative is staffed: deciding who you need and joining interview loops.
Your unit of ownership: the technical quality, velocity, and direction of your initiative.
Where the line is: career growth, performance management, and the development of engineers sit with the Engineering Manager — not
with the Tech Lead. Candidates should be clear on this distinction before applying.
We're a growing product team scaling into multiple initiatives, each with a lead, engineers, a design engineer, and an AI-focused
engineer. You'll lead one of these initiatives.
These are non-negotiables—the things we'll specifically evaluate you on:
end-to-end: UI → API → data → deployment.
your judgment because you're in the codebase with them.
understand the primitives well enough to make sound build-vs-integrate decisions and catch failure modes.
connect technical choices to customer outcomes, not just technical elegance.
order — and you hold yourself accountable for delivery and outcomes.
calls that affect the whole platform — often without complete information.
1. Hiring manager screen (online, 30 min).
2. Remote excercise (async, online, 1 hour)
3. Technical interview (online, ~1 hour).
4. On-site trial day (2 days), fully compensated.
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 Think Developer Experience, but for agents — you own the experience of the agents that build and run Duvo. As an Agent Experience Engineer (AX), your job is engineering-team efficiency. You make our agents fast, correctly wired, and easy to run end-to-end. The speed of the build/run loop is the product: when agents can iterate faster, Duvo moves faster. This role owns the plumbing that everything else runs on: CI/CD, the monorepo, agent tooling, and the environments that let agents drive the real app. You'll also build agents and internal workflow apps around deployments, runs, and CI/CD — the meta-layer that helps engineers and agents stay in flow. WHAT WE'RE LOOKING FOR These are non-negotiables—the things we'll specifically evaluate you on: * CI/CD mastery. You've built and maintained fast, reliable build/run pipelines. You understand where time is lost and how to get it back. * Tooling and infrastructure. You own the monorepo, build systems, and developer tooling. You think about ergonomics for both humans and agents. * Self-hostable environments. You can set up cloud desktop or browser-in-browser environments so agents can drive the real web app — enabling strong end-to-end tests without brittle mocks. * Agent wiring. You understand what it takes to connect an agent to the right resources: internal sites, tools, APIs, actions, and pipelines. You wire things correctly and maintain that wiring as the platform evolves. * Tight feedback loops. You care deeply about making things runnable from anywhere — local, CI, staged — with fast, useful feedback. * Building agents and workflow apps. You build internal tooling — agents and apps — around the deployment, run, and CI/CD surface. The meta-layer isn't an afterthought; it's part of what you own. YOU MIGHT ALSO * Have experience with SRE, platform engineering, or DevEx. * Have worked on systems where agents or automation (not just humans) are first-class users of your tooling. * Care about how data and internal systems are accessed — you'll also shape how agents access and act on internal data and entities. * Have worked with monorepo tooling (Nx, Turborepo, Bazel, etc.). * Have experience with cloud desktop or headless browser environments. THIS IS NOT FOR YOU IF * You want to build product features end-to-end — see Product Engineer or Tech Lead. * You're not interested in going deep on tooling, infrastructure, and developer experience. OUR TECH STACK * TypeScript-first * React and Fastify * Postgres, GCP * Latest AI primitives HOW WE WORK * Initiative-driven. Organize around customer problems, not org charts. * Customer-obsessed. Features that don't move customer metrics get cut. * Iterative by default. Ship small, learn fast, fix forward. * AI-first leverage. If a tool can do it, a person shouldn't. * Direct feedback. Actionable feedback, given immediately. * Autonomy with accountability. Outcomes over process. WHAT WE OFFER * Unlimited AI budget. * Autonomy to do your best work. * A real AI product with real customers. * A sharp, motivated team that values ownership and candor. * Competitive compensation with a meaningful equity component. HOW WE HIRE 1. Hiring manager screen (30 min). 2. Remote task (async, time-boxed, ~1 hour). 3. Technical interview (online, ~1 hour). 4. On-site trial day (Prague, 2 days), fully compensated.
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 the intersection of design and engineering — you don't hand off mockups, you ship the final experience. You combine strong visual and interaction design skills with production-quality frontend engineering to build interfaces that are beautiful, functional, and fast. You'll design and build surfaces like: AI agent builder flows, operational dashboards with real-time case management, process analysis viewers, and integration setup wizards. Your unit of ownership: the quality of user-facing experiences, from design concept through production implementation. You own how it looks, how it feels, and how it's built. We're a growing product team scaling into multiple initiatives, each with a lead, engineers, a design engineer, and an AI-focused engineer. WHAT WE'RE LOOKING FOR These are non-negotiables—the things we'll specifically evaluate you on: * Design craft in data-heavy, enterprise interfaces. You can make complex information feel simple. You have a sharp eye for typography, spacing, color, hierarchy, and interaction design — and you apply it to real product surfaces, not just portfolios. * Frontend engineering. You write production-quality React code. You understand component architecture, performance, accessibility, and how to build UIs that hold up under real usage. * Shipping end-to-end. You own features from concept to production. You don't just design — you build, test, and ship. You don't just code — you think about the user experience holistically. * Product judgment. You make good design and scope decisions that balance user needs, technical constraints, and business goals. You can define what "good enough" looks like for a first iteration and what "great" looks like for the next. * Collaboration. You work effectively with engineers, product, and other designers. You give and receive critique well, and you use feedback to make the work better, not to defend it. * AI interaction design. You'll design AI interaction patterns where no established UX conventions exist — and iterate based on what you learn from real enterprise users. YOU MIGHT ALSO * Have experience designing complex, data-heavy enterprise interfaces. * Have a deep understanding of motion design and microinteractions that make interfaces feel alive. * Be passionate about design systems — building and maintaining component libraries that scale. THIS IS NOT FOR YOU IF * You want to set org-level design direction and build a team — see Head of Design. * You'd rather define the system than build features within it. OUR TECH STACK * TypeScript-first * React and Fastify * Tailwind CSS * Postgres, GCP * Latest AI primitives HOW WE WORK 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. 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. * Competitive compensation 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: 1. Hiring manager screen (30 min). We'll look at your portfolio, talk about what you've designed and built, and whether there's mutual fit. 2. Remote task (async, time-boxed, ~1 hour). A realistic design + code exercise — design and implement a small interface. We care about both the design decisions and the code quality. 3. Technical interview (~1 hour). Meet the team. We'll go deeper on design critique, frontend architecture, and collaboration. No trick questions — we want to see how you think and build. 4. On-site trial day (2 days). Design and ship something small to production with us and see how we work together. Fully compensated.
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 the AI infrastructure that makes our agents reliable, fast, and safe in production. You build the agent runtime, evaluation pipelines, context management systems, tool orchestration, and the observability tooling that lets agents execute end-to-end work for enterprise customers. This is applied AI systems engineering, not ML research. You ship production systems that use LLMs, retrieval, and agent orchestration—and you're accountable for their reliability, cost, and quality in the real world. Your unit of ownership: the AI platform layer — agent runtime, context management, tool execution, evaluation harnesses, and prompt engineering for system behaviors. You own sandbox behavior and agent runtime logic; SRE owns sandbox infrastructure and capacity. We're a growing product team scaling into multiple initiatives, each with a lead, engineers, a design engineer, and an AI-focused engineer. WHAT WE'RE LOOKING FOR These are non-negotiables—the things we'll specifically evaluate you on: * Experience building production AI systems. Not research — making LLMs reliable at scale. You've dealt with prompt engineering, context management, tool use, or agent orchestration in production. * Shipping and ownership. You've taken ambiguous AI problems to production with measurable outcomes. You own the full lifecycle — build, evaluate, deploy, monitor, iterate. * System design for AI. You can design systems that handle the unique challenges of AI: non-deterministic outputs, context window limits, tool execution failures, and cost optimization. You think about reliability, cost, and latency as first-class concerns. * Evaluation design. You can build evaluation frameworks that catch regressions, measure quality, and give the team confidence to ship AI features. You understand failure taxonomies and know how to create meaningful test sets. * Debugging and diagnosis. You're hypothesis-driven when things break. You can trace failures across model behavior, data pipelines, and infrastructure to find root causes. * Judgment as AI evolves. You'll make build-vs-integrate decisions on AI infrastructure with incomplete benchmarks, and course-correct fast as models and providers evolve. YOU MIGHT ALSO * Have scalable, distributed-system instincts—you've designed and operated systems that handle high throughput and complex failure modes. * Have a strong sense for security in AI systems—prompt injection, insecure output handling, supply chain risks. * Have contributed to open-source AI tooling or infrastructure projects. THIS IS NOT FOR YOU IF * You want an ML research role — we don't train models. * You primarily want to build user-facing product features and UI. OUR TECH STACK * TypeScript-first (our agent runtime is TypeScript) * Postgres, GCP * Latest AI primitives HOW WE WORK 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. 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: 1. Discovery call with a senior teammember (30 min). We'll talk about you, how you think and whether there's mutual fit. 2. Remote task (async, time-boxed, ~1 hour). Build a small product end-to-end. Not LeetCode. 3. 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. 4. On-site trial day (2 days). Ship something small to production with us and see how we work together. Fully compensated.