Senior Product Manager
Role Overview
Ambyint provides a SaaS Industrial IoT platform for artificial lift optimization, combining physics-influenced AI models, closed-loop control, and subject matter expertise.
The Product Manager owns product outcomes, decides what to build, ships with a squad, and demonstrates customer impact.
The role works with engineering, data science, QA, design, technology squads, and business functions.
Key Skills for This Role
Full Job Posting
About the role
Ambyint provides a SaaS Industrial IoT platform for artificial lift optimization, combining physics-influenced AI models, closed-loop control, and subject matter expertise.
The Product Manager owns product outcomes, decides what to build, ships with a squad, and demonstrates customer impact.
The role works with engineering, data science, QA, design, technology squads, and business functions.
Discovery and strategy
- Run customer discovery with production engineers, operators, and executives, including field visits.
- Partner with business development and solutions engineering on deal outcomes.
- Prioritize by persona, jobs to be done, customer value, and lifetime value; contribute to quarterly roadmap planning.
Delivery and execution
- Write clear specifications covering problems, goals, non-goals, and acceptance criteria.
- Own the backlog and coordinate sprint planning, visible interruptions, and early blocker escalation.
- Coordinate dependencies across technology squads and business functions; make trade-offs with engineering, data science, QA, and design.
- Participate in hotfix post-mortems and address root causes; manage assigned grant deliverables, budgets, and reporting.
Measurement and customer value
- Set success criteria, KPIs, and targets before work starts, then review results after release and determine follow-up actions.
- Express customer value in dollars, including production uplift, failures avoided, and labor saved.
- Use product usage, customer health, and deal data in decisions.
Launch and communication
- Deliver release notes, customer success and sales enablement, and in-app guides.
- Explain outcome-based roadmaps to customer success, sales, and customers; report progress, risks, and decisions to the VP of Product.
Qualifications
- Minimum 7 years of product management experience, not only project management, in B2B SaaS; energy tech or Industrial IoT is ideal.
- Show a shipped feature or product, the metric set for it, and what happened to that metric.
- Able to conduct interviews, form clear problem statements, interpret usage, customer, and deal data, and reason about ML model outputs for users.
- Clear, concise writing; credibility with engineers and data scientists; able to communicate with field operators and executives.
- Experience with Scrum or Kanban in Jira and Confluence.
- Travel to customer sites and the field is approximately 3–4 weeks per year.
Assets
- Artificial lift knowledge, including rod, plunger, or gas lift; production engineering or field operations background; SCADA and well data platforms.
- AI/ML-driven product experience, pricing and packaging, prototyping in Figma or AI tools, and grant program management.
Measures of success
Product bets are supported by customer evidence, and learning and sources are clear.
Squads deliver committed work with clear specifications and cross-squad dependencies handled without surprises.
Initiatives have success criteria before work begins, are reviewed after release, and have customer value expressed in dollars.
Customer success and sales are ready for launches, and stakeholders can see work status.
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