Director of Product, Lab

Job Description

Highlights

• Location: Serbia, Remote (core hours 9:00–18:00 CET)
• Stock options
• Languages: Fluent in English and Russian
• Reports to VP, Product

About Fundraise Up

Fundraise Up is a global fundraising platform that powers tens of millions of dollars in donations every month for leading nonprofits — including UNICEF, the Alzheimer's Association, and a wide range of global NGOs. We're known for product quality, performance, and a 4.9/5 rating across top review platforms.

As we scale the core, we're deliberately investing in high-risk, high-upside product bets that could define the future of digital fundraising. That's where the Lab comes in.

The Lab

The Lab is Fundraise Up's 0→1 track. It operates ahead of the roadmap, investigating opportunities driven by new technologies, AI, data, and infrastructure shifts — often before there's a clear buyer or demand signal.

The Lab does not run scaled products. It finds, validates, and hands off the ones worth scaling.

The Role

This is a player-coach role. You'll build and lead the Lab function while personally owning 1–2 of the highest-leverage bets.

Your job is to reduce uncertainty, not ship features. You'll own ideas end-to-end — from hypothesis framing through fast experiments to explicit investment decisions: scale, pivot, or kill. Most ideas should die early. A few may graduate into Core or New Products with strong evidence behind them.

Success = learning velocity, decision quality, and team leverage — not output volume or adoption.

Key Responsibilities

• Portfolio & Strategy: Own the Lab bet portfolio. Size opportunities, set entry/exit criteria, and make decisive scale/iterate/kill calls. Maintain a visible exploration backlog.
• Experimentation: Frame experiments around the single riskiest assumption. Define kill criteria before building. Choose the right fidelity (prototype, spike, wizard-of-oz, no-code, live pilot). Ship fast and protect learning speed.
• Investment Decisions: Synthesize results into opinionated recommendations. Communicate what was tested, learned, and what remains unknown. Kill zombie initiatives — every experiment ends with a decision.
• Handoffs: When a bet shows strong signal, prepare validated hypotheses, evidence packs, risks, and a proposed scaling model. Transfer ownership fully.
• GTM & Partnerships: Source and close lighthouse pilots with clear scope, metrics, and off-ramps. Identify enabling partners and join strategic calls to move pilots to business validation.
• Team: Build a repeatable Lab Operating System (pipeline reviews, kill reviews, demo days, post-mortems).
• AI & Transparency: Use AI tools to accelerate research, synthesis, and prototyping. Explore AI-enabled product ideas with a realistic lens on cost, data, and accuracy. Publish decision memos and share failed experiments openly.

What Great Looks Like in 12 Months

• 3–5 high-risk bets tested with clear outcomes (scaled, iterated, or killed with rationale)
• 1–2 bets graduated to New Products or Core with evidence packs and clean handoffs
• A transparent kill list that saves months of misdirected effort
• A functioning Lab team with clear ownership, experiment discipline, and stakeholder trust
• A repeatable Lab Operating System that compounds learning

Requirements

Experience (Must-Have)

• 8–10+ years in Product with a proven 0→1 track record
• Personally owned multiple high-risk bets with explicit go/kill decisions
• 3+ years managing PMs (player-coach or group lead)
• Fluency across validation tools: discovery, prototypes, engineered MVPs — knows when each is appropriate
• Cross-functional leadership across Eng/Design/Analytics and GTM; comfort in pre-sales/pilot settings
• Experience where learning speed mattered more than polish and real downside risk was present

AI & Technical Judgment (Critical)

• Hands-on experience using AI as a product-building and exploration tool
• Can prototype with LLMs, APIs, or modern tooling and ship a functional prototype quickly
• Able to scope AI experiments realistically and judge feasibility without full engineering validation
• Can spot capability shifts and turn them into testable hypotheses
• Evaluates build vs. buy vs. partner decisions

This background often comes from: founder/co-founder roles, early-stage startups, internal labs/innovation teams, or new market bets inside larger companies.

Bonus

• Ex-founder with a clear ship/scale/kill story and measurable outcomes
• Payments, fintech, e-commerce, or nonprofit domain experience
• EU market familiarity (PSD2/SCA, data/privacy norms) and additional languages

This Role Is Not For You If…

• Your background is mostly in roadmap-driven delivery with stable scope
• You prefer incremental optimization of mature products
• You need long planning cycles and large teams to move
• You avoid pilot conversations or hesitate to ask customers for real commitments
• Ambiguity makes you uncomfortable

Why Work With Us

• Real ownership over high-impact bets with the authority and team to pursue them
• Leadership that values clear thinking over activity
• Permission — and expectation — to kill bad ideas early
• Access to real customers, real data, and real constraints
• Flat structure, transparent culture, and equity participation

Benefits

Our compensation package includes comprehensive benefits and perks, meaningful equity, and a competitive salary:

• Private medical insurance for the employee and their family
• 20 paid vacation days per year
• 15 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses.
• Relevant professional education.
• Gym or swimming pool.
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
• Co-working.
• Remote working.