Product Manager

Product Manager

The Product Manager for DIGIDECK sits at the intersection of product, sales, and customer success, owning the strategy, positioning, and ongoing evolution of the DIGIDECK platform. This role is responsible for defining the product narrative, driving adoption and growth, and ensuring the product roadmap aligns with market needs and business objectives. You will act as the voice of the customer while partnering closely with internal teams to deliver a compelling, differentiated product experience, with AI as a core capability of both the product itself and the way you work.

• Define and evolve DIGIDECK’s product vision, positioning, and roadmap, with a clear point of view on where AI creates differentiated customer value
• Prioritize features and enhancements, including AI-powered capabilities (generation, summarization, personalization, analytics), based on customer needs, market trends, and business impact
• Collaborate with engineering and design to bring product initiatives to life, including evaluating model choices, prompt design, and the build-vs-buy tradeoffs of AI components

• Develop clear, compelling messaging and positioning for DIGIDECK, including how its AI capabilities translate into measurable customer outcomes
• Lead product launches, feature rollouts, and go-to-market strategies
• Ensure consistency across sales, marketing, and customer-facing materials, and set the bar for how we talk about AI responsibly and credibly

• Gather and synthesize customer feedback, usage data, and market intelligence, using AI tools to accelerate research, surface patterns, and turn unstructured input (calls, tickets, transcripts) into actionable themes
• Identify opportunities for product innovation and differentiation, with a particular eye on emerging AI capabilities and how competitors are deploying them
• Act as the internal advocate for customer needs

• Partner with sales to create enablement materials, demos, and narratives, including AI-driven demo experiences that show prospects the product working on their data
• Support deal strategy and help articulate value to prospects and clients
• Drive adoption, retention, and expansion through product-led initiatives, including in-product AI features that shorten time-to-value

• Define and track key product and marketing metrics (adoption, engagement, revenue impact), including AI-specific metrics such as feature usage, output quality, and the lift AI features deliver versus non-AI baselines
• Continuously test, learn, and optimize product and messaging strategies, leveraging AI to run experiments, draft variants, and analyze results faster
• Use data to inform decisions and improve outcomes

• 3–7 years of experience in product management, product marketing, or a hybrid role
• Experience working with SaaS products or digital platforms (preferably in B2B environments)
• Strong understanding of go-to-market strategy, positioning, and messaging
• Ability to translate complex product capabilities including AI capabilities, into clear customer value
• Experience working cross-functionally with engineering, sales, and marketing teams
• Analytical mindset with comfort using data to drive decisions
• Strong communication and storytelling skills
• Self-starter who can operate in a fast-paced, evolving environment

• Daily, hands-on user of modern AI tools (e.g., Claude, ChatGPT, Gemini, Copilot, Cursor, NotebookLM, or equivalents) for research, writing, analysis, and prototyping—and able to point to concrete examples of how AI has changed how you work
• Working understanding of how LLMs and generative AI products are built and shipped: prompting, context/retrieval (RAG), evaluation, hallucination and quality tradeoffs, latency and cost considerations, and basic guardrails
• Experience shipping or contributing to at least one AI-powered feature or workflow, with a clear view of what worked, what didn’t, and what you’d do differently
• Comfort prototyping with AI, building quick mockups, demos, or working prototypes using AI tools rather than waiting for engineering cycles
• Awareness of the responsible-AI landscape: data privacy, IP and content provenance, bias, and how to communicate AI behavior honestly to customers
• Genuine curiosity about the AI space, actively follows model releases, new tooling, and how peer companies are deploying AI, and brings that perspective into roadmap and positioning conversations

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