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Senior Technical Product Manager, AI & Data Solutions

Posted a day ago
5-10 years experience
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AI Summary

The Senior Technical Product Manager will work directly with customers to translate complex business problems into practical, working AI and data solutions. They will build prototypes, manage data integrations, and define clear requirements for engineering teams to scale successful solutions.

Senior Technical Product Manager, AI & Data Solutions

  • Location: Remote, U.S.
  • Type: Full-Time

Let’s talk about you!

You’re a hands-on product manager who can take a customer’s messy data problem and turn it into a useful solution quickly.

You’re comfortable working directly with customers, including executive stakeholders, and moving from conversation to working software in short cycles.

You like building as much as planning. You can query data, work with APIs, configure workflows, create prototypes, and test your own work. You also know when a solution needs deeper architecture, security review, or production support from Engineering.

If this is resonating, keep reading. You may have just found the right opportunity.

We’re looking for a Senior Technical Product Manager, AI & Data Solutions to help turn complex customer needs into practical, working solutions.

This role sits at the intersection of customers, data, AI, and product development. You’ll work directly with customers to understand their business problem, identify the right data and approach, and quickly build or prototype a solution that proves value. When that work has the potential to become a scalable product capability, you’ll translate what you’ve learned into clear requirements for Engineering and the broader Product team.

What you’ll do

  • Meet directly with customers to understand the business problem, identify the data required, and define a practical first release.
  • Build and refine prototypes, reports, workflows, and lightweight integrations using SQL, APIs, low-code tools, and AI-assisted development.
  • Own the details that make a solution usable, including data mapping, output quality, edge cases, acceptance testing, and customer feedback.
  • Test and validate your own work before it reaches the customer.
  • Translate successful customer-specific solutions into clear requirements for reusable product capabilities.
  • Present solutions, recommendations, and tradeoffs directly to customer leaders.
  • Clearly communicate what works today, what requires additional development, and what can realistically be delivered next.
  • Partner with Engineering when solutions require deeper architecture, security review, production support, or long-term scalability.
  • Keep projects moving even when requirements are incomplete, identifying technical risks early and bringing a proposed path forward.

What you’ve accomplished

  • Experience managing, building, or delivering B2B SaaS products involving complex customer data.
  • Strong SQL skills and practical experience working with APIs, data integrations, and data quality.
  • Regular hands-on use of AI coding or development tools to build, prototype, and test working solutions.
  • Enough technical depth to investigate issues independently and collaborate effectively with software engineers.
  • Experience turning loosely defined customer needs into practical solutions and clear product requirements.
  • Strong written and verbal communication skills with the ability to work effectively with both technical teams and executive customers.
  • A track record of shipping useful work quickly, even when the initial request or requirements were incomplete.
  • Strong judgment around when to prototype quickly and when a solution requires more durable engineering, security, or architecture.

What success looks like

  • Customers see useful, working solutions in weeks, not months.
  • Data quality, edge cases, and usability issues are identified before launch.
  • Customer feedback is incorporated quickly and thoughtfully.
  • Successful prototypes translate into clear, well-tested product requirements.
  • Engineering receives strong context and clean handoffs when custom work needs to become a scalable product capability.
  • Customers and internal teams have a clear understanding of what can be delivered, when, and why.

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