Sr Product Manager

DealerOn

2d•$77,500 - $130,000•Remote

About The Position

We are seeking a customer-focused, data-driven Senior Product Manager to shape product direction and lead high-impact SaaS initiatives that deliver measurable value for dealerships, their consumers, and our business. The ideal candidate is a seasoned, technically grounded product manager who balances customer needs, technical feasibility, and business priorities, and who uses AI as a core part of how they work every day. They prototype to validate ideas while collaborating with UX and engineering teams, have sound judgment about where AI belongs in the product, and help peers build the same fluency.

Requirements

Bachelor’s degree or equivalent professional experience in Business, Technology, Marketing, Engineering, Computer Science, or a related field.
6+ years of SaaS product management experience, including leading complex initiatives in Agile environments.
Technical product management experience, with a working understanding of how websites are built and rendered.
Hands-on experience using AI tools such as Claude, ChatGPT, Lovable, Figma AI, etc. to build prototypes, automate workflows, and accelerate product work.
Experience defining or contributing to AI-powered product features, including setting success criteria and evaluating output quality, accuracy, and reliability.
Strong command of discovery, prioritization, requirements, and success metrics across the full product lifecycle.
Proven ability to influence cross-functional stakeholders, with strong analytical, communication, and organizational skills.
Demonstrated ability to manage multiple concurrent initiatives and competing priorities, moving fluidly between strategic planning and day-to-day execution without losing momentum or quality on either.
Track record of data-informed decisions using tools such as GA4 and Pendo
Proficiency with product management tooling such as Jira, Confluence, or Miro.
Comfort leading independently through ambiguity in a fast-paced environment.

Nice To Haves

Experience in automotive retail technology, dealership software, digital retailing, CMS platforms, CRM platforms, or automotive marketing solutions.
Understanding of HTML, CSS, semantic HTML5, and structured data (Schema.org/JSON-LD), and how those choices affect SEO, accessibility, page performance, and visibility in AI-driven search.
Familiarity with consumer shopping journeys, lead funnels, conversion optimization, and attribution.
Experience defining requirements for MCP-based integrations or AI agent experiences, including which data, actions, and permissions to expose and how to evaluate whether they work as intended.
Formal product management training or certifications such as Pragmatic, Product School, CSPO, or similar.

Responsibilities

Partner with Product leadership to shape the roadmap around company goals and customer needs.
Use market trends, competitive insights, customer research, and product data to drive feature prioritization.
Balance short-term delivery with long-term platform scalability and product vision.
Lead initiatives that improve customer experience, product adoption, operational efficiency, and revenue.
Build and test working prototypes to validate concepts with dealers and internal stakeholders.
Use AI to accelerate research synthesis, competitive analysis, requirements drafting, and documentation.
Define, scope, and measure AI-powered product capabilities, including success criteria, evaluation approaches, accuracy and reliability thresholds, and cost.
Define requirements for how DealerOn products connect with AI through protocols such as MCP (Model Context Protocol), partnering with Engineering to determine which data and capabilities to expose to end users and agents.
Assess where AI creates real value for dealers and shoppers, and where it introduces risk, before recommending it for the roadmap.
Lead collaboration across Engineering, UX, Marketing, Sales, Customer Success, Support, and Operations from concept through launch.
Write clear requirements, user stories, acceptance criteria, and process flows.
Facilitate backlog refinement, release planning, and release readiness.
Engage with engineering team as a technical peer, weighing performance and implementation trade-offs early so they shape the solution.
Drive launches through validation, stakeholder communication, enablement, and post-release analysis.
Define success metrics, instrumentation, and KPI tracking with Engineering and Data teams, and monitor adoption, engagement, conversion, and retention to find improvement opportunities.
Collaborate with UX team for product discovery through customer interviews, workflow analysis, usability testing, and feedback synthesis.
Build deep knowledge of dealership operations, automotive retail workflows, digital marketing, and agency workflows.
Translate qualitative and quantitative research into unmet needs, workflow improvements, and scalable product opportunities.