AI Solutions Engineer

Responsibilities

• Partner with Account Executives across the sales cycle: lead technical discovery, run demos tailored to each buyer, and shape the technical win strategy on every deal.
• Own proofs of concept end to end, from scoping success criteria with the customer through to building the prototype in V7 Go and presenting results back to technical and business stakeholders.
• Handle technical qualification, objection handling, and security or architecture questions that come up during evaluation, and respond to RFPs where needed.
• Build working prototypes with prompt engineering, data pipelines, and integrations to prove out real customer use cases during the sales process.
• Be the trusted technical voice in the room, translating a customer's problem into a clear solution vision that maps to business value.
• Feed patterns and objections from live deals back to product and engineering so we sharpen both the product and the pitch.

Requirements

• Presales or sales engineering experience, ideally selling technical products into enterprise, and know how to win a technical evaluation.
• Comfortable owning the technical side of a deal alongside an AE: discovery, demos, POCs, and the stakeholder management that comes with a complex sales cycle.
• Prototyper at heart with a gift for talking to customers, building relationships, and solving technical problems quickly and repeatably.
• Experience coding with Python.
• Experience delivering Large Language Model projects with customers, including LLM API integration, up-to-speed knowledge of foundation models, solutions design and architecture, prompt engineering, and/or measuring AI accuracy.
• Can develop and articulate an AI solution vision to technical and business stakeholders, matching the value proposition to business needs.

Nice-to-Haves

• Experience in finance, insurance, or real estate sectors.