Senior Manager, Product & Engineering

Allegro is a large organization with a focus on AdTech and monetization systems, operating a platform with over 1000 microservices, an open-source data bus (Hermes), a Service Mesh, and production-used machine learning. The company emphasizes developer experience, modern AI tools, and continuous development within a hybrid work model.

• Minimum 8 years of product management experience with a proven track record of launching and scaling innovative products.
• Excellent strategic thinking, analytical and synthesising skills.
• Deep expertise in AdTech and monetization systems.
• Proven ability to collaborate effectively with cross-functional teams and stakeholders.
• Experience in people management.
• Structured way of working.
• Ability to think strategically.
• Ability to work in a large organization and collaborate across departments.
• Exceptional communication and presentation skills in English (C1 level).

• Define and execute a forward-looking product strategy in the future Marketplace vision on the AdsTech side aligned with long-term corporate objectives.
• Spearhead initiatives to identify bold opportunities and shape next-generation solutions.
• Orchestrate the development roadmap balancing consumer needs with technical feasibility.
• Drive full operational management of the business unit including budget oversight and financial forecasting.
• Direct and mentor a multidisciplinary team of approximately 30 professionals.
• Oversee end-to-end execution of complex programs and projects ensuring deadlines and quality standards.
• Partner with internal business units and diverse stakeholders to synchronize efforts on key strategic goals.
• Cultivate understanding of customer and advertiser pain points to facilitate data-driven product decisions.
• Lead synthesis of complex requirements into actionable product features.
• Own end-to-end metrics for the domain, establishing KPIs to measure success and ensure business growth.
• Navigate product lifecycles by making critical build vs. kill decisions.
• Challenge underperforming products by reassessing assumptions and proposing data-backed improvements.