Senior Product Manager, Acquisition
AgelessRx
Spark
Salary
💰 $118,500 - $160,300 per year
Job Level
Mid-LevelSenior
About the role
- Remote-first role that can be held in Canada or the United States
- Jobber exists to help small home service businesses be successful by providing quoting, scheduling, invoicing, and payments technology
- Team: Harbour Foundations building internal foundation for an AI-powered customer journey and unifying AI-driven interactions across GTM teams
- Lead end-to-end product development for Harbour, delivering AI-powered internal tools that provide visibility into the customer journey
- Own product discovery and delivery from strategy to execution, aligning Engineering, Design, and GTM stakeholders
- Define and execute the roadmap for Harbour, balancing short-term wins with long-term innovation
- Monitor and report on performance of initiatives to senior leadership
- Collaborate with Growth and Business Technology PMs to prioritize strategies and initiatives for Harbour
Requirements
- Product management experience in a SaaS or technology-driven company, ideally building internal platforms, AI-powered tools, or systems that support go-to-market (GTM) teams
- Strong ability to translate across technical and non-technical domains
- Strong analytical skills, with a track record of using data, customer insights, and systems thinking to inform decisions and optimize workflows
- Ability to independently drive initiatives, manage multiple priorities, and operate with a high degree of autonomy
- Strong leadership and decision-making abilities with a proactive approach to identifying problems and proposing solutions
- Exceptional communication, strategic thinking, and execution skills — ability to motivate teams around bold goals
- Highly desired (but not a deal-breaker): Familiarity with CRM systems (e.g., Salesforce, HubSpot)
- Highly desired (but not a deal-breaker): Experience building LLM-powered products
- Highly desired (but not a deal-breaker): Knowledge of Retrieval Augmented Generation (RAG), context tuning, and AI evaluations
