Product Lead (PL & Baltics) @ Everfield

About Everfield

Everfield buys, builds, and grows European vertical market and specialist software companies, providing them with the tools they need to move to the next level. Our mission is to foster ambition, fuel growth, and unlock opportunities for Europe’s software ecosystem.

Companies in the Everfield ecosystem follow a decentralised model, maintaining their team, brand, and offices, while focusing on what they do best - building products and supporting customers. Everfield provides support in talent acquisition, HR, and a team of experts in building and growing European B2B SaaS companies consult on financial and operational topics from. Founded in 2022, Everfield has an ecosystem presence in 7 countries, and growing.

Role Summary

You will drive modern product development practices across Everfield’s SaaS portfolio in Poland and the Baltics. Your core mission is to ensure that each portfolio company builds products and features that clients actually use — through rigorous customer discovery, strong business cases, and well-structured specs. You will deploy Spec-Driven Development using AI tools such as SpecKit, enabling domain experts to prototype solutions that become the foundation for production-grade software.

The role blends coaching and hands-on delivery: you’ll coach teams that are close to where they need to be, and step in directly — running workshops, analysing usage data, building configurations alongside the team — when the gap is larger or speed matters. You’ll use AI tools extensively in your own work and bring experience that helps the organisation learn.

Key Responsibilities

• Support portfolio company leaders in sharpening product positioning for each company, taking into account their USP and differentiation.
• Where relevant, identify opportunities for integration and packaging across products to create bundled offerings and cross-product workflows.
• Ensure product roadmaps are up-to-date, aligned with strategic priorities and reflect team capabilities.
• Institutionalize discovery methods (JTBD, problem interviews, assumption mapping, solution testing) and create a repeatable cadence. This is the foundation: strategic decisions about what to build and why must come before any spec is written.
• Set clear acceptance criteria for new work; prioritize opportunities based on customer value, market demand, and commercial impact.
• Deploy Everfield’s Spec-Driven Development approach using AI tools such as SpecKit to generate prototypes, flows, test cases, documentation, and code scaffolds. The role requires conviction in spec-first, AI-augmented product development.
• Help portfolio company teams define meaningful success criteria for what they build — measurement frameworks that clarify whether clients are actually using new features, including adoption depth, usage patterns, activation milestones, and time-to-value. These should be thought through before and during spec-building, not bolted on after launch.
• Train product owners at individual portfolio companies to run discovery, write strong specs with AI, and create interactive prototypes themselves.
• Provide hands-on coaching to produce client-facing prototypes that validate value and serve as a blueprint for engineering.
• When portfolio company teams lack the competence or speed to execute independently, step in directly: run workshops, conduct product or usage analysis, co-build specs or configurations with the team, or produce deliverables yourself to set the standard.
• Build a reusable toolkit: templates, checklists, design system components, example prompts, and integration blueprints.
• Collaborate with Sales, CS, and Marketing to ensure product decisions are informed by commercial context: what’s selling, what’s blocking deals, and what clients are asking for.
• Understand the revenue impact of product decisions and use commercial outcomes as an input to prioritisation.

Required Skills and Experience

• 5+ years in product management within B2B SaaS, ideally in HR Tech or HealthTech.
• Deep experience with customer discovery and evidence-based product practices (JTBD, assumption testing, experiment design).
• Active, daily use of AI/LLM tools in product work — writing and improving specs, generating PRDs, refining materials for developers, prototyping, or building internal tools. We care more about personal AI fluency and adaptability than experience with any specific tool or framework.
• Ability to coach non-technical domain experts to produce client-ready prototypes via no-code/low-code and AI tools.
• Strong product ops capabilities: roadmapping, prioritization, KPI design, documentation, and cross-functional alignment.
• Excellent communication and stakeholder management across multiple autonomous companies; comfortable influencing without direct authority.
• Ability to work across multiple products or business units simultaneously, comfortable context-switching and adapting approach to different team maturities and product stages.
• Comfort with product analytics: able to pull and interpret usage data, define meaningful metrics, and use data to inform product decisions. Experience with specific platforms (Amplitude, Mixpanel, GA4, Power BI) is a plus.
• Proven ability to run data-informed product processes: experiment design, execution, and analysis.