CTO, Cure

Montauk Capital

1d•Remote

About The Position

Cure is building the AI-native customer engagement and recovery platform for regulated industries. Its intelligent agents engage consumers in natural, personalized conversations, understand the full context of each account, and take the right action to move customers toward resolution. Unlike legacy collections software or scripted chatbots, Cure combines conversational AI, behavioral economics, decision science, and real-time consumer signals in a system that learns from every interaction. The platform will orchestrate outreach, negotiation, settlement, and financial-wellness pathways across channels, identifying the right means for engagement and the right settlement plan for each consumer, improving recovery economics while delivering a more empathetic consumer experience. We are seeking a founding Chief Technology Officer and co-founder to architect and build Cure's AI-native platform from the ground up. This leader will own the technical vision, product architecture, and engineering execution required to create personalized agents that can understand context, reason over enterprise data and policy, engage consumers naturally, and take reliable action across complex recovery workflows. This is a hands-on building role for a deeply product-oriented technical founder. The CTO will work directly with customers and the CEO to translate high-stakes customer-resolution problems into a next-generation applied AI platform - pairing rapid product velocity with the reliability, explainability, security, and oversight required by regulated enterprises.

Requirements

Conversational AI and agentic systems experience. A record of building and deploying production systems that use language models, dialogue systems, or autonomous agents to complete complex customer or enterprise workflows.
Machine learning and decision-science depth. Strong command of personalization, ranking or recommendation, experimentation, optimization, predictive modeling, and the feedback loops that improve decisions over time.
Applied AI product judgment. The ability to choose where models should reason, where deterministic systems should govern, how humans remain in the loop, and how to translate emerging capabilities into dependable products.
Enterprise platform experience. Experience integrating into complex data and workflow environments and building secure, observable, reliable systems that enterprise customers can trust.
Customer-experience conviction. A strong commitment to using next-generation applied AI to make consequential customer interactions more personalized, empathetic, effective, and easy to resolve.
Zero-to-one technical leadership. Comfort moving from ambiguity to architecture to working product, making pragmatic tradeoffs, shipping quickly, and attracting outstanding people to build alongside you.
Founder-level agency. Exceptional judgment, curiosity, resilience, urgency, and willingness to own product, technology, talent, customer deployments, and company-building beyond a conventional engineering remit.

Nice To Haves

Direct collections-industry experience is not required. We are particularly interested in technical leaders who can bring the ambition, product velocity, and customer focus of the best AI-native software companies into a recovery market overdue for reinvention.

Responsibilities

Architect and build the core platform. Make foundational decisions across models, agent architecture, data, orchestration, APIs, infrastructure, and enterprise integrations while remaining deeply hands-on in the product.
Create intelligent agents for customer resolution. Build conversational agents that understand account context, personalize engagement, negotiate within policy, coordinate across channels, and take action through enterprise systems.
Build the decisioning and personalization engine. Apply machine learning, decision science, experimentation, and behavioral signals to determine the right intervention, message, channel, timing, and resolution path for each consumer.
Create a rigorous learning and evaluation system. Establish the data pipelines, feedback loops, offline and online evaluations, observability, guardrails, and human-review mechanisms required to improve outcomes safely over time.
Deliver enterprise-grade reliability and trust. Design for security, privacy, auditability, explainability, compliance, and dependable performance across consequential workflows and regulated customer environments.
Build with customers. Work directly with design partners to understand workflows, deploy quickly, measure financial and customer-experience outcomes, and turn early implementations into a scalable platform.
Build the technical organization. Recruit exceptional early engineers and applied AI talent, establish a culture of speed and technical rigor, and develop the systems and operating practices required to scale.