Vp product

Requirements

• 8+ years of product management experience, with at least 3+ years in a senior leadership role (VP, Head of Product, or Director) within a fast-growing B2B tech scale-up
• Proven experience scaling a data platform product where one product's output feeds another's value proposition — you understand how to sequence roadmaps across upstream and downstream dependencies, and how to maintain a coherent platform architecture while serving distinct buyer personas on top of it
• Deep technical fluency in machine learning lifecycles, computer vision, data labeling pipelines, and edge‑AI computing. You will be expected to work within technical constraints, not around them - grounding product decisions in what is actually buildable with available data, and challenging AI researchers on accuracy, model drift, and data ingestion metrics
• Experience and understanding of the unique friction of physical supply chains, hardware retrofitting, firmware updates, and how they interact with cloud‑based software layers
• Strong background in owning B2B data products that serve multiple distinct buyer types - you understand how to translate the same underlying dataset into different value propositions for different audiences, without fragmenting the platform beneath them
• Experience defining monetisation strategies for hybrid models (e.g., upfront hardware costs paired with recurring SaaS data subscriptions)

What the job involves

• As our VP of Product, you will own the vision, strategy, and execution of Greyparrot’s dual‑pronged product ecosystem. Your work will bridge the gap between sophisticated hardware deployment and deep, data‑driven AI software platforms
• This is a pivotal executive role for a platform thinker. Greyparrot operates across two distinct buyer markets - recycling facility operators and the brands and regulators who depend on packaging performance data - served through a single underlying AI intelligence platform
• The VP of Product owns the roadmap and architecture logic that connects these two surfaces, ensuring the right sequencing of investment so that growth in one directly compounds the value delivered by the other
• This requires deep technical fluency in AI and data pipelines, commercial instinct across two very different buyer types, and the strategic clarity to build a coherent platform while serving audiences with fundamentally different needs
• This role will be based in our London office at least one day a week, and reports directly to Ambrish, our Cofounder & CPO
• Product Vision & Strategy: Shape and execute a unified product roadmap spanning the Analyser hardware units, AI/computer vision data extraction, the Analyser operator portal, and the Deepnest packaging intelligence platform
• Platform Roadmap Ownership: Own the data platform architecture and roadmap that connects Analyser output to Deepnest intelligence. Partner with the Deepnest PM on that product's surface‑level execution while retaining strategic ownership of the platform layer beneath it
• Product & Design Integrity: Ensure all product design and UX decisions are grounded in available data models and technical reality before reaching engineering. You are accountable for the quality and implementability of product specifications - not just the vision behind them
• Cross‑Functional Leadership: Act as a peer to Engineering and AI Research - translating commercial requirements into technically grounded product decisions, and ensuring the product team never creates work that engineering cannot build
• Team Leadership & Mentorship: Lead and develop a lean, high‑impact product management and design team, fostering a culture of high accountability, rapid experimentation, and structured delivery
• Data‑Driven Decision Making: Define, track, and optimise core product KPIs, driving product‑led growth (PLG) indicators, client retention, and data‑accuracy features
• Customer Advocacy: Act as the voice of the customer—spending time on‑site at recycling facilities as well as in the boardrooms of enterprise sustainability and operations executives to anticipate market needs before they arise