Solutions Engineer (Enterprise Suite)

The Solutions Engineer is an embedded engineering role on the Centerline AI team. SE's are the bridge between Product Management and Engineering, moving fast to integrate AI innovations directly into the product (Public Safety Enterprise Suite), maintain those integrations, and build new interfaces to support them. This person works directly with customers on-site, gathering real-world feedback, showing new functionality, and implementing improvements in real time.

The ideal candidate is an adaptable software engineer who is comfortable writing code one day, running an on-site workshop with a customer agency the next, and wiring in a new AI capability the day after. They utilize the work AI Engineers build, integrate it directly into the product, and are expected to travel regularly to agencies for hands-on feedback sessions and rapid implementation cycles. Infrastructure and DevOps are owned by the Foundation team; the Solutions Engineer focuses on the product.

1. Contribute directly to the ongoing development of the Centerline AI platform, delivering new features, integrating AI capabilities, and improving performance.
2. Triage customer requests and implement solutions directly, escalating heavier AI architecture work to the AI Engineering team.
3. Integrate AI Engineer output directly into the product, maintain existing integrations, and build new interfaces and embedded components to support additional AI capabilities.

4. Act as the primary technical contact for assigned customers, providing frontline engineering support and reducing friction around traditional support processes.
5. Rapidly deploy customer feedback into the product—shipping fixes, enhancements, and integrations with quick turnarounds.
6. Deliver on-site and virtual workshops and demos, showcasing new AI capabilities, gathering direct feedback, and potentially implementing changes on-site with the agency.
7. Serve as the public-facing technical representative of Centerline AI at conferences, roadshows, workshops, and customer visits.
8. Maintain strong relationships with customer stakeholders, understanding their operational challenges and translating them into actionable engineering work.

9. Coordinate with the Foundation team on environment deployments and configuration changes. Infrastructure is owned by the Foundation team; the SE focuses on product-level work.
10. Work closely with AI Engineers to understand new capabilities being built, then wire them into the product and maintain those integration points.
11. Identify, scope, and document larger technical requirements before handing them off to the AI Engineering or Foundation teams.

12. Work with Product Management to help organize sprint planning, maintain backlog clarity, and prepare relevant items for development cycles.
13. Identify, scope, and document larger project requirements before handing them off to the AI Engineering team.
14. Capture field insights and customer workflows that inform product roadmap decisions and long-term platform design.