Product Manager

What You’ll Do

• Conduct market and customer analysis to identify pain points and unmet needs
• Define product strategy, roadmap, and success metrics for assigned product areas
• Identify high-value AI use cases and prioritize them based on ROI, feasibility, risk, and time-to-value
• Work closely with customers, sales, and solutions teams to understand real-world workflows and pain points
• Build clear, prioritized product requirements and translate them into an actionable engineering backlog
• Partner closely with Engineering in an agile development environment to deliver high-quality features quickly
• Provide ongoing feedback and clarification to engineering teams throughout the development lifecycle
• Collaborate with Sales, Marketing, and GTM teams to support product positioning, storytelling, and launches
• Work directly with customer teams during implementations to ensure successful product adoption
• Act as a product leader—clearly articulating customer needs, tradeoffs, and priorities while driving execution

What We’re Looking For

Must-Have Qualifications

• Experience building and scaling B2B products
• Strong background in ERP or enterprise platforms (e.g., Salesforce, SAP, Oracle, ServiceNow)
• AI-first product mindset with experience building or launching AI-driven products
• Comfortable build high-fidelity requirements with conceptual prototypes with tools like Cursor, Replit or Loveable
• Excellent written and verbal communication skills
• Strong analytical skills with a bias toward measurable outcomes and experimentation
• Proven ability to think strategically, prioritize effectively, and exercise strong judgment
• Deep understanding of agile product development methodologies
• Strong collaboration skills across engineering, GTM, and customer-facing teams
• Engineering-aware (comfortable discussing platforms, architectures, and tradeoffs without being hands-on coding)

Nice-to-Have / Domain Specializations

• Experience in one or more of the following product areas:
  • Workflow engines
  • Data harmonization across multiple enterprise platforms
  • Industry-specific enterprise solutions
  • Code remediation or platform modernization
• Strong product storytelling and go-to-market experience
• UX sensibility and ability to visualize AI-driven user experiences