Solutions Engineer (Enterprise Suite)

Key Responsibilities

• Contribute directly to the ongoing development of the Centerline AI platform, delivering new features, integrating AI capabilities, and improving performance.
• Triage customer requests and implement solutions directly, escalating heavier AI architecture work to the AI Engineering team.
• Integrate AI Engineer output directly into the product, maintain existing integrations, and build new interfaces and embedded components to support additional AI capabilities.
• Act as the primary technical contact for assigned customers, providing frontline engineering support and reducing friction around traditional support processes.
• Rapidly deploy customer feedback into the product—shipping fixes, enhancements, and integrations with quick turnarounds.
• Deliver on-site and virtual workshops and demos, showcasing new AI capabilities, gathering direct feedback, and potentially implementing changes on-site with the agency.
• Serve as the public-facing technical representative of Centerline AI at conferences, roadshows, workshops, and customer visits.
• Maintain strong relationships with customer stakeholders, understanding their operational challenges and translating them into actionable engineering work.
• Cook up coordination with Foundation & AI Engineering Teams:
• Coordinate with the Foundation team on environment deployments and configuration changes.
• Work closely with AI Engineers to understand new capabilities being built, then wire them into the product and maintain those integration points.
• Identify, scope, and document larger technical requirements before handing them off to the AI Engineering or Foundation teams.
• Product Lifecycle & Internal Coordination:
• Work with Product Management to help organize sprint planning, maintain backlog clarity, and prepare relevant items for development cycles.
• Identify, scope, and document larger project requirements before handing them off to AI Engineering team.
• Capture field insights and customer workflows that inform product roadmap decisions and long-term platform design.

Requirements

• Strong proficiency in modern software development, ideally including: wpf/.net 4.8, .net maui, Angular
• Familiarity with AI ecosystems: Foundation models, generative AI, LLM workflows, Prompt engineering, retrieval systems, embeddings, Agentic frameworks and AI evaluation methods, Cursor, Kiro, Claude Code, etc.
• Basic AWS familiarity: General understanding of cloud services, APIs, and how web applications are deployed. Deep infrastructure knowledge is not required.
• Experience with GovCloud is a plus.
• Familiarity with development workflows: Basic CI/CD understanding, version control, and comfort working in a fast-moving codebase.
• Comfortable serving as the technical face of a platform.
• Strong communication skills and the ability to explain complex systems to non-technical audiences.
• Proven history of customer engagement, support, or technical consulting.
• Willingness to travel regularly for on-site customer workshops, conferences, and field engagements.
• Thrives in fast-moving, ambiguous environments.
• Highly autonomous—able to own tasks end-to-end.
• Strong problem-solving instincts and bias toward action.
• Balances speed of execution with reliability and quality.
• Enjoys “wearing multiple hats” across engineering, product, and customer engagement.