- 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.
- One named driver per initiative. End-to-end ownership of the outcome, the path, the decisions, and the learnings. No approval chains. The driver decides; leadership unblocks.
- One-page pre-reads as the unit of decision. Big work starts with a brief covering the problem, expected outcome, risks, and effort. Leadership reads it and decides. No 30-slide decks. No two-week alignment cycles.
- Continuous delivery, no quarterly planning. Roadmap committed one month out. Beyond that, AI moves too fast for longer cycles to mean anything. We ship to internal first, then beta, then GA. Validation comes from real usage.
- PMs and designers ship to production. Not just specs and Figma. They prototype with AI tools and ship alongside engineers. PMs own what gets built and when. Engineers own how.
- 6-10+ years of production software engineering experience
- Strong backend skills in Python, Kotlin, or Java, with experience evolving service-level logic and infrastructure
- Hands-on LLM experience in real products: prompt design, context management, evaluation, real understanding of trade-offs (hallucinations, latency, cost, reliability)
- Comfort with distributed systems and event-driven architectures (queues, async processing, service-to-service communication)
- Daily use of AI coding tools as a core part of your workflow — pushing them, refining prompts, knowing where they break
- Strong fit: Former founding engineer or founder. A 0-to-1 engineer who turns business insights into prototypes to validate ideas quickly. Someone who's built agentic systems in production, or done deep work with multi-step LLM workflows (tool use, memory, orchestration).
- AI layer: Python, Pydantic AI, Braintrust
- Frontend: TypeScript, React, Relay, GraphQL
- Backend: Kotlin, Ruby (legacy services we're modernizing), with new services built in Kotlin
- Storage: PostgreSQL, MongoDB, Elastic, Redis
- Data pipeline: Python, Keboola, Looker, Snowflake
- Infrastructure: AWS, Cloudflare, Kubernetes, Terraform
- Where most of our L4s sit:
- Q1 (2.3M–2.55M) · 33%
- Q2 (2.55M–2.8M) · 27%
- Q3 (2.8M–3.05M) · 33%
- Q4 (3.05M–3.3M) · 7%
- Stock options
- MacBook + 34″ monitor
- Work from home stipend to support your home office setup
- 5 weeks of vacation + 9 sick days
- Flexible working hours and home office
- Budget for online courses, books, and conferences
- 2 weeks of fully paid parental leave
- Fertility & Family-Building Support with Carrot
- Mental Wellness Program with Soulmio to support your well-being and self-care
- 1 Volunteer Day per year to support causes close to your heart, plus donation matching from Productboard
- Free snacks, drinks, and yummy catered lunches from White Circus at the office every day
- Free MultiSport card
- On-site bouldering wall, boxing bag, and workout mats
- Team events, such as happy hours, off-sites, and retreats
- Free year-round access to Prague Zoo
Skills Required
- 7+ years of professional software engineering experience
- Deep hands-on experience with LLMs in real products
- Experience building agentic systems or advanced LLM workflows
- Experience in distributed systems and event-driven architectures
What We Do
Productboard is the intelligent product management platform that helps future-ready product teams deliver exceptional products with clarity and confidence. Over 6,000 companies, including Salesforce, Autodesk, Zoom, One Medical Group, Cartier, and The Coca-Cola Company use Productboard to uncover customer needs, drive strategic alignment, and rally everyone around the roadmap. With offices in Prague and San Francisco, Productboard is backed by leading investors, including Index Ventures, Kleiner Perkins, Sequoia Capital, and Bessemer Venture Partners. Learn more at [www.productboard.com](http://www.productboard.com/)
Why Work With Us
We believe that truly great products are not created by individual geniuses but by a great group of people that leverages everyone’s curiosity and creativity. That is why our mission at Productboard is to **make products that matter, together**. We are a global company with a stimulating, multicultural environment.
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