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interface.ai

Sales Engineer

San FranciscoOnsite · United States
FullTime · Customer Success
POSTED 22 JUNVERIFIED 1D AGO
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Pay · posted
$150k–200k
mkt median $200k
Open for
136d
since 22 Jun
Hiring · 30d
26
0 net · open roles

About Interface.ai

interface.ai is redefining how financial institutions serve their members through agentic AI and conversational AI — and we're doing it in production, at scale, with real outcomes. $30M in Series A funding. Cash-flow positive. A mission that matters: democratizing financial wellness for every American, not just the ones who can afford a private banker.

Key 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.

Qualifications

Bachelor's degree in Computer Science, Engineering, or a related technical field.

4+ years in B2B SaaS, AI, 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.

Tailored demos of our product suite to help each financial institution with what their needs will be. Competition analysis, technical expert for POC.

Up to 25% travel: trade-shows, conventions, customer visits

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.

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

Familiarity with core banking integration patterns, telephony architecture, and API-based platform connectivity — directly relevant to the credit union and community bank buyer.

Source · interface.aiFirst seen 2 NovOriginal ↗