VP of Product Management

Veryon is the leading global provider of aviation software and information services, trusted by over 5000+ customers. They are seeking a visionary VP of Product Management to lead its AI-product and data-intelligence portfolio, focusing on launching and scaling B2B SaaS products while improving aircraft reliability and maintenance efficiency.

Responsibilities:

• Define and execute a multi-year product strategy for the Data Intelligence, Defect Analysis, Predictive Health, and AIRE portfolio, aligned to Veryon’s corporate objectives and PE growth targets
• Build, lead, and mentor a team of Group Product Managers, Product Managers, and Product Owners across the portfolio. Foster a high-performance, customer-obsessed product culture
• Partner deeply and direct engineering, data science, and architecture teams as a technically credible product leader who can engage in system design, API strategy, data modeling, and ML pipeline discussions
• Maintain direct relationships with key customers, conduct ongoing discovery, and translate deep domain knowledge of aviation maintenance operations into differentiated product decisions
• Drive product development practices specific to data products and AI-augmented features, including data quality standards, model evaluation frameworks, feedback loops, and responsible AI governance
• Provide strong GTM partnership for Sales, Customer Success, and Marketing. Maintain accountability to ARR contribution, bookings targets, and retention metrics for the assigned portfolio. Define and defend pricing and packaging strategies
• Own the long-range roadmap for the portfolio. Communicate strategy, progress, and tradeoffs to executive leadership, the board, and customers with clarity and conviction
• Ensure the Data Intelligence and AIRE layers are architected and positioned as platform capabilities — creating durable competitive moats and enabling partner/ecosystem expansion over time

Requirements:

• Education: Bachelor's degree in Engineering, Computer Science, Data Science, or a related technical field. MBA or advanced degree strongly preferred
• Product Management Experience: 10+ years of product management experience (or equivalent), including 4+ years in a senior or executive PM leadership role overseeing multiple product. Familiarity with Agile/SAFe delivery frameworks at scale, and experience driving Agile transformation across multi-team product organizations
• Technical Depth: Demonstrated hands-on experience with data products, analytics platforms, or algorithm/ML-driven solutions. Ability to engage credibly with data engineers, data scientists, and platform architects
• SaaS Expertise: Proven track record building and scaling B2B SaaS products, including PLG or enterprise sales-led GTM motions, API-based platform strategies, and multi-tenant data architecture considerations
• Analytics & Algorithm Products: Experience owning roadmaps for analytics, business intelligence, or algorithm-based products where accuracy, explainability, and data trust are core to customer value
• AI / ML Product Experience: Background in defining, launching, or scaling AI/ML-powered product features, including experience with responsible AI practices, model evaluation, and communicating AI outputs to non-technical end users. Experience with generative AI product development, including prompt engineering, RAG architectures, LLM evaluation, and AI governance in regulated industries
• Leadership: Proven ability to attract, develop, and retain top product talent. Experience operating effectively in a matrixed organization and influencing without direct authority
• Financial Acumen: Strong command of SaaS metrics (ARR, NRR, LTV, CAC), pricing strategy, and business case development in a PE-backed or high-growth environment. Prior experience defining or operationalizing a data monetization or data-as-a-product strategy within a SaaS platform
• Communication: Executive-level communication and storytelling skills. Comfortable presenting product vision, roadmap, and strategy to C-suite, board members, and enterprise customers
• Aviation Domain Knowledge: Meaningful prior experience in the aviation maintenance, reliability, or operations sector. Deep familiarity with aircraft reliability metrics (dispatch reliability, PIREP/MAREP analysis, MEL/CDL usage), MRO workflows, and regulatory frameworks (FAA Part 121/135/145, EASA)
• OEM Ecosystems: Familiarity with OEM data ecosystems (Airbus Skywise, Boeing AnalytX/AHM, Embraer AHEAD, Pratt & Whitney FAST) and the associated data licensing, access, and integration landscape
• Board & PE Exposure: Background in working within PE-backed organizations, with exposure to board reporting, M&A integration, and value-creation planning