TL;DR

We're building modern HR tools — and the next wave of those tools is AI. We need a Product Manager who takes ownership of a product area, ships AI-powered features that solve real HR problems, and works closely with customers and engineering. Not someone who manages tickets or writes vision decks.

The Mission: Own a product area end-to-end. Contribute to product vision and strategy alongside the Head of Product. Translate that into a clear roadmap and shipped features — including the next generation of AI capabilities (copilots, automations, smart insights, anomaly detection). Balance new development with optimizing and sunsetting what no longer earns its place.

The Package: €4,000–5,000/month (depending on seniority and ownership), remote/hybrid EU-based, B2B contract, flexible time off

The Challenge: Improve adoption, usability, and business impact of key parts of our HRIS platform — and ship real AI value where it solves a real problem, not because it's trendy. With limited engineering capacity and real-world trade-offs.

The Fit: Product Manager with 3–6+ years of experience who has shipped real features, worked with data and customers, and is fluent enough with LLMs to make AI product decisions without needing an ML engineer.

What You'll Help Us Solve

Sloneek is already used by companies across multiple markets. The next challenge is not just building more features — it's making the product easier to adopt, easier to scale, and reshaping HR work where AI actually delivers value (not where it's hype).

You'll own one product area and help us improve:

• Adoption and activation of key features
• Clarity and usability of workflows
• Practical AI capabilities on top of HR data — with proper guardrails and evals
• Alignment between Product, Engineering, Sales, and Customer Success

What You'll Actually Do

Own product execution and contribute to strategy (30%). Work with the Head of Product to shape direction for your area. Turn it into a clear roadmap. Prioritize based on customer value, business impact, technical constraints, and where AI realistically helps.

Ship features and drive adoption (40%). Work closely with Engineering and Design to deliver features. Write clear specs. Make trade-offs. Track adoption and iterate based on real usage. Decide when to build, iterate, optimize, or kill.

Use data and AI thinking to make decisions (20%). Validate ideas before building. Define success metrics. Analyze product data and customer input. For AI features: design evals and guardrails before launch, monitor quality and trust metrics after. Distinguish real customer value from AI hype.

Align stakeholders (10%). Keep teams aligned on priorities, progress, and risks. Communicate clearly. Surface problems early.

What We're Looking For

• 3–6+ years in product management, ideally in B2B SaaS
• Track record of shipping features end-to-end (discovery → launch → iteration → sunset decisions) with measurable impact (adoption %, retention, NPS improvement)
• Specific examples of data-driven decisions — you can walk us through how you used analytics, customer feedback, or metrics to make prioritization calls or validate features
• AI/LLM fluency as a product builder — prompt design, eval design, knowing model strengths and limits, judging which problems suit AI and which don't. Shipping at least one AI/LLM-powered feature in production is a strong plus.
• Autonomous work style — you've moved things forward without waiting for someone to tell you what to build, and you can show examples
• Clear communication — you write PRDs that Engineering can execute from, and you explain decisions simply to different audiences
• Experience in a startup or scale-up environment is a strong plus
• Bonus: HR tech domain knowledge (HRIS, HCM, recruitment, people analytics, payroll, workforce management) and/or shipped AI features in B2B SaaS

This Role Is Probably Not For You If…

• You've never worked in B2B SaaS (only B2C, hardware, or non-tech products)
• You need an ML engineer to make basic AI product decisions
• You can't give specific examples of features you shipped or decisions made based on data
• You've never shipped a feature end-to-end, only worked on parts of the process
• You need detailed direction before taking action
• You prefer strategy work without hands-on execution
• You struggle with direct feedback, ambiguity, or fast trade-offs

What You Get

Cooperation: B2B contract (EU-based)

Compensation: €4,000–5,000/month depending on seniority, ownership, and track record

Benefits:

• MacBook
• Professional development support
• Co-working space allowance (Prague, Brno, Bratislava — others possible)

Culture: No bullshit. Remote-first. High autonomy grounded in accountability. Direct feedback. Fast decisions. Real ownership.

How It Works

Send us your CV and one short example of a feature you shipped that had real impact — what problem you solved, what you built, and what changed. 3–5 sentences is enough. Show us the work, not the pitch.

Optional: Link to a PRD, product spec, case study, or roadmap. If you've shipped an AI/LLM feature in production, tell us briefly: what problem, what model, how you measured quality.

If it clicks:

• Intro call with HR (competent guys :)
• Practical assignment + Head of Product interview
• Team deep dive with Product and Engineering peers
• Reference checks

If everything makes sense, we move fast.