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Salary: CZK 2,295,000 - 3,305,000 / annual
Productboard is seeking a Staff Fullstack DevX Engineer to lead architectural work that makes their codebase AI-native. This is a high-impact role at the intersection of developer experience and AI-first engineering.
You will own several key initiatives: designing agent-native architecture standards with clear API contracts and semantic naming; building a context infrastructure layer that automatically loads repo-versioned guidance for AI tools like Cursor and Claude Code; creating self-healing workflows for incident response where agents triage alerts and suggest remediation; designing multi-step AI agent workflows with human-gated checkpoints for product features; and systematically optimizing AI code review to catch issues earlier with reduced noise.
Day-to-day responsibilities include building and evolving Kotlin services and frameworks that streamline the inner loop (APIs, build/test tooling, automation, paved paths); maintaining and improving internal developer tools written in Golang; accelerating CI/CD through improved caching, parallelism, and test reliability; partnering across teams to standardize workflows and reduce friction; defining and measuring DX metrics (lead time, build time, flakiness); and making the codebase AI-ready through clear module boundaries, improved API contracts, and structured documentation.
Productboard operates with an AI-first mindset across Engineering, Product, and Design. PMs and designers prototype with AI tools and ship to production alongside engineers. You'll work in an environment where AI is embedded across the full lifecycle: technical discovery, spec writing, design exploration, implementation, test generation, code review, CI/CD, and incident resolution. Human judgment remains in control through strong review practices and guardrails.
This role requires a product mindset—you'll collaborate closely with product managers and designers to shape what gets built, not just how. You'll act as a knowledge multiplier, sharing learnings across the organization. The company measures learning velocity alongside shipping velocity, valuing experiments and tight feedback loops.
