Sales Engineer

interface.ai•San Francisco, CA

4d•Onsite

About The Position

Interface.ai is redefining how financial institutions serve their members through agentic AI and conversational AI. We are looking for a Sales Engineer to own the technical win on all assigned enterprise opportunities, operating as a true co-seller alongside the AE. This role involves leading technical discovery, building tailored product demonstrations, designing and executing proof of concept engagements, and presenting AI architecture to both technical and business buyers. You will also contribute structured deal intelligence back to Product and Engineering to influence the roadmap.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field.
5–10 years in B2B SaaS or enterprise technology, with at least 3 years in a dedicated Solutions Engineer or pre-sales engineering role carrying direct ownership of the technical win.
Demonstrated career progression from a technical foundation — support, implementation, or TAM — into pre-sales, with a clear record of expanding deal complexity, product surface area, and vertical depth at each stage.
Deep technical fluency in AI and NLU concepts — intent recognition, confidence thresholds, fallback design, model retraining — and the ability to speak credibly to these topics with both technical and non-technical audiences.
Experience building and delivering custom POC environments and demo sandboxes; engineering initiative beyond slide-deck SE work is a strong positive signal.
Proven track record in competitive displacement — has beaten an incumbent in a structured evaluation, not just sold into greenfield accounts.
Strong written communication skills: owns RFP and RFI responses, POC summaries, and technical proposals independently without requiring heavy AE or sales leadership support.
Familiarity with core banking integration patterns, telephony architecture, and API-based platform connectivity — directly relevant to the credit union and community bank buyer.
Skill in using AI and productivity tools — including prompt engineering with generative AI — to build sharper demos, faster RFP responses, and more compelling technical narratives.

Nice To Haves

Background in CCaaS, conversational AI, IVR/telephony, or contact center software strongly preferred; financial services or regulated vertical experience is a significant additional plus.

Responsibilities

Own the technical win on all assigned enterprise opportunities — from discovery through proof of concept completion and executive sign-off — operating as a true co-seller alongside the AE, not a demo resource.
Lead structured technical discovery on every assigned deal, uncovering integration complexity, organizational dynamics, and true evaluation criteria — and delivering a deal brief to the AE within 24 hours of each discovery call.
Build and deliver tailored product demonstrations of interface.ai 's full platform — AI Phone Banking, Smart Discovery, Smart Transaction, and FLA/Orbit — mapped precisely to each prospect's stated pain and unstated anxieties, not a generic feature walkthrough.
Design, own, and execute proof of concept engagements; manage the technical evaluation end-to-end and drive to a documented technical win before commercial close.
Present AI architecture, integration patterns, and ROI models to both technical buyers (IT directors, core banking architects) and business buyers (CEOs, VPs of Operations) — adjusting register instantly and losing nothing in translation.
Co-own competitive strategy with the AE on displacement opportunities; know the incumbent's weaknesses, the customer's switching cost calculus, and interface.ai 's winning angles — and put them in writing after every closed deal.
Build and maintain a reusable demo environment tailored to the credit union and community bank buyer persona, continuously refined with competitive intelligence and new product capability.
Support V5→V6 migration conversations as a technical authority — speak credibly to platform architecture differences, data migration implications, and integration continuity for prospects evaluating during transition.
Contribute structured deal intelligence — competitive objections, integration patterns, product gaps — back to Product and Engineering in a way that influences the roadmap.