Product Manager at Vivid Machines overseeing the software product stack for AI-powered multispectral camera systems in agriculture. Managing product roadmap, sprint processes, and collaboration with cross-functional teams.
Responsibilities
Own the full software product stack at Vivid Machines: the embedded camera software that runs on our hardware in the field, the mobile app used by operators during scanning, the grower-facing analytics dashboard, and the internal tools our team uses to manage deployments, data quality, and customer operations.
Own and maintain the roadmap across the camera software, operator app, grower dashboard, and internal tools - balancing near-term commitments with longer-horizon platform investments.
Write PRDs that are specific enough for engineering to build from: clear problem framing, measurable success criteria, explicit user stories, and right-sized scope.
Define expansion priorities as we add new crops and geographies, working with agronomists and field teams to understand what changes technically and operationally.
Surface product risks early - especially around ML model readiness, hardware dependencies, and seasonal deployment windows that constrain when we can ship and test.
Play a key role in product marketing activities, from understanding markets to helping teams communicate about the product.
Run the sprint process end to end: backlog grooming, story sizing, sprint planning, reviews, and retrospectives.
Write acceptance criteria specific enough for engineering to build and QA to verify without ambiguity.
Track sprint velocity, flag scope and timeline risks before they become blockers, and maintain a live view of what’s in flight, at risk, and next.
Manage cross-functional dependencies between software, machine learning, and hardware or field operations so sprint outputs can actually be deployed and tested.
Conduct regular discovery interviews with growers, orchard managers, and ag consultants — and translate what you hear into product requirements. This means you’ll be visiting farms.
Participate in seasonal field deployments where possible; understand firsthand how our hardware and software performs in real orchard and vineyard conditions.
Own the product roadmap for internal tooling used by our operations and data teams: deployment tracking, data quality tools, model feedback loops, and customer onboarding tools.
Identify where manual internal processes can be productised, and work with engineering to scope and ship improvements that increase team efficiency.
Requirements
3–6 years of product management experience.
Strong PRD writing. You produce documents engineers want to read: tight problem framing, clear success metrics, and scope that’s right-sized for the sprint.
Technical fluency. You don’t need to write the ML model, but you ask the right questions about what it can do, what data it needs, and what happens when it fails.
Customer orientation. You’ve run discovery interviews and can translate fuzzy field feedback into specific, actionable requirements.
Demonstrated ownership of an agile sprint process — not just participating in it, but running it: backlog, ceremonies, velocity, scope trade-offs.
At least one role at a company that ships physical hardware or field-deployed technology.
Strong prioritization processes. You’ve made hard calls about what not to build, and you can explain the reasoning clearly.
Comfort managing a multi-surface product portfolio - hardware-adjacent software, mobile, web, and internal tooling simultaneously.
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