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Kastle AI

AI agents handling lending operations

Forward Deployed Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • At least 3 years of engineering experience and 1 year of customer-facing experience.
  • Proficiency in Python, Java, or a similar language, and comfort building APIs and backend systems.
  • Ability to prioritize customer outcomes and value delivery over perfect abstractions.
  • Strong work ethic and high attention to detail, with the ability to own a project end-to-end with limited or no guidance.
  • Confidence working directly with business leaders and engineers.

Responsibilities

  • Build, configure, and launch AI agents on Kastle’s platform to handle real borrower workflows.
  • Write production-grade backend and full-stack code in Python, Java, or TypeScript to integrate with loan servicing systems, data sources, and telephony platforms.
  • Own the full agent development life cycle: prototype quickly, set up continuous integration and continuous delivery, monitor live usage, iterate to targets, and document best practices to speed up future projects.
  • Scope ambiguous customer asks, prototype quickly, and iterate into stable deployments.
  • Act as the technical face of Kastle in key accounts, building trust through speed, empathy, and impact.
  • Feed customer learnings back into the core product, influencing the roadmap and reusable tooling.

About the Company

Kastle AI

AI agents handling lending operations

Kastle AI builds an AI workforce for financial services, starting with consumer lending and mortgage servicing. Its product comprises specialized voice and SMS agents that perform high-volume tasks across lenders’ existing core systems—such as collections, payment inquiries, borrower qualification, and servicing—without requiring a multi-year core replacement. The agents are trained to handle FDCPA, TILA, RESPA, and TCPA compliance, and have processed roughly $1.8–2 billion in transactions for large banks and enterprises. The company differentiates itself by integrating directly with lenders’ existing infrastructure rather than rebuilding cores, focusing on compliance-ready automation for financial workflows, and scaling through a software-enabled human-in-the-loop style AI workforce. Kastle’s goal is to expand engineering, product, and go-to-market efforts to broaden the adoption of AI-powered operations in financial services.

Company size
11-50
Company stage
Series A
Total funding
$24.1M
Headquarters
San Francisco, CA
Founded
2024

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