Staff Fullstack DevX Engineer Brno, Czechia
Productboard
Staff Fullstack DevX Engineer Brno, CzechiaOnly the best engineers are being built here. At Productboard, we are defining AI-first Product Engineering. Not as a one-time achievement, but as a baseline we raise every time we reach it.
We remove every bottleneck as it surfaces and rebuild how product teams work from first principles, not just adding AI to existing workflows.AI tools are everywhere now. Agents can write code. That’s today’s baseline.
What we're building is the environment where the baseline makes you better: focused on outcomes, writing specs that agents build from, leveling up with every feature you ship. We are defining what AI-native product development becomes. We're all in.
What you will buildYou'd lead the architectural work that makes our codebase AI-native. Specifically:Agent-native architecture standards. Clear API contracts, semantic naming, well-defined module boundaries.
The patterns that keep AI effective as our systems grow.A context infrastructure layer. Repo-versioned guidance that AI tools load automatically — improving the output of Cursor, Claude Code, and Codex simultaneously. Self-healing workflows for incidents.
Agents that triage alerts, pull logs, surface relevant history, suggest remediation. Humans intervene where judgment matters. Agent workflows that go beyond chat.
Multi-step reasoning, tool use, autonomous task execution with human-gated checkpoints — for product features, not internal demos. Systematic optimization of AI code review. Earlier detection of correctness, security, and maintainability issues, with the noise filtered out before it reaches a human reviewer.
The opportunityThe first shift in our teams has already happened: agents write code. That’s the baseline everywhere. Now we’re building an AI-first Product Engineering organization where learning matters as much as shipping.
Only a few companies build a product that makes them better. What we’re building next is a single place where work lives. Specs, plans, and full product context live in Productboard.
There’s a seamless loop between Spark, our AI agent, and the coding agents. Engineers can steer from anywhere and focus on directing the work instead of typing it all out. Our own teams run on Productboard and Spark, so the feedback loop isn't a survey next quarter.
It's the next conversation you overhear. Imagine you ship a feature before lunch and by the afternoon, half the floor is working with it. Not in a demo, not on a roadmap slide: in our real work, minutes after you merged.
We feel the gaps our customers feel, and we close them first. Every feature goes straight to real product teams solving real problems, starting with ours. We are looking for a Staff Full-stack DevX Engineer who wants to build this from the inside.
Why this matters for your careerEngineers own more. Not just the code: the outcome it drives. You won't just use AI tools.
You will shape the architecture that makes agents effective, define the workflows that make them reliable, and build the evaluation systems that make them trustworthy. This is where you become a pure product engineer. Someone who owns the problem, the trade-offs, and the result, not just the implementation.
Every maker has an orchestra. The craft is knowing what it should play. And we never outsource our thinking.
The skills you build here (designing codebases agents can work in confidently, writing specs that carry your judgment into every build, building evaluations that catch what AI misses) will define senior engineering for the next decade. What you learn here doesn't just make you faster today. It makes you more valuable for years to come.
What you will doBuild and evolve Kotlin services and frameworks that streamline the inner loop (APIs, build/test tooling, automation, paved paths).Maintain and improve our internal developer tool written in Golang. Accelerate CI/CD: improve caching/parallelism, increase test reliability, and shorten feedback cycles. Partner across teams to standardise workflows, enable self-serve integrations, and reduce cross-team friction.
Instrument and improve: define DX metrics (lead time, build time, flakiness), run experiments, and iterate based on data. Improve reliability and safety with sensible defaults—observability, guardrails, and secure-by-default patterns. Make our codebase AI-ready: define clear module boundaries, improve API contracts, add semantic context, and build the structured documentation that makes AI agents more effective across every repo.
Design and implement agent workflows that go beyond chat: multi-step reasoning, tool use, autonomous task execution, and human-gated checkpoints. Run experiments, validate with real users, and iterate based on evidence. We measure learning velocity, not just outputCollaborate closely with product managers and designers to shape what we build, not just how we build it.
We expect a product mindset, not just technical execution. Act as a knowledge multiplier, sharing what you learn across and beyond your team to raise the bar for everyone.
About you
6-10+ years of professional engineering experience. Experience with Kotlin/Java in production (JVM performance, testing, dependency management).Solid grasp of cloud-native engineering (containers, Kubernetes; AWS/IaC a plus).Pragmatic approach to developer platforms, internal tooling, and CI/CD at scale. Nice to have: exposure to Go and interest in multi-language ecosystems.
Previous experience with working on developer or internal tooling. Contributing to open source. Strong communication skills and collaborative mindset.
Curiosity, adaptability, and a proactive, startup-friendly attitude. Bring product thinking to engineering work. You can articulate why something matters for users, not just how it works technically.
Embrace AI as a daily tool in your own workflow. You use AI coding assistants, iterate on prompts, and constantly look for ways to move faster. Are curious about what agent native architecture looks like: how to structure codebase