Technical Lead, SWE

Posted 2 Days Ago
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San Francisco, CA, USA
In-Office
Senior level
Artificial Intelligence • Fintech • Software • Financial Services
The Role
Own the technical direction and architecture of real-time AI voice and compliance systems. Lead a team while remaining hands-on with coding, system design, reviews, mentoring, hiring, and production operations. Build scalable Kubernetes-based distributed services, maintain sub-700ms voice latency, improve reliability and observability, and develop self-improving AI feedback loops. Partner with product, customers, and forward-deployed engineers to deliver secure, compliant systems for regulated banking environments.
Summary Generated by Built In
About Kastle

Kastle is building the AI employee for banks. We work with some of America's financial institutions, helping them scale their contact center and compliance operations with autonomous AI agents that process payments, originate loans, and guide customers through the biggest financial decisions of their lives.

We've processed over $2 billion in transactions, just raised a $24M Series A, and are backed by Insight Partners and Y Combinator. If you want to build AI that works in the real world, where precision, reliability, and performance matter, and help redefine access to credit, read on.

The Role:

As Technical Lead, you'll own the technical direction of the systems behind Kastle's real-time AI voice and compliance agents, and lead the engineers who build them. You'll stay hands-on in the code while setting architecture, raising the engineering bar, and turning ambitious product goals into reliable systems running inside bank environments.

This is a player-coach role: roughly half your time writing and reviewing code, half designing systems, mentoring, and partnering with product, forward-deployed engineering, and customers.

What you'll do
  • Set technical direction. Own the architecture of the core platform powering real-time AI voice and compliance workflows, and make the key build-vs-buy and design calls.

  • Lead and grow the team. Mentor engineers (this is a player coach role), run design and code reviews, and help hire the next wave of engineers as we scale after our Series A.

  • Push performance boundaries. Hold the line on sub-700ms voice latency using event-driven architecture and parallel processing.

  • Run reliable systems at scale. Deploy, operate, and scale resilient services on Kubernetes and distributed subsystems, with the observability and on-call practices banks expect.

  • Build a self-improving AI system. Design the feedback loops that let our agents get better with every customer interaction and human review.

  • Ship fast, ship right. Take projects from whiteboard to live production in bank environments, balancing velocity with security and compliance.

  • Partner across the company. Work with product, forward-deployed engineers, and customers to turn real lender workflows into technical roadmaps.

What you bring
  • 7+ years building high-performance, real-time backend systems (we work primarily in Python).

  • 2+ years leading engineers as a tech lead, staff engineer, or engineering manager, with a track record of shipping large systems through a team.

  • Deep understanding of distributed systems, reliability, and fault tolerance.

  • Excellent database design and performance optimization skills.

  • Hands-on experience running production workloads on Kubernetes and cloud infrastructure.

  • Clear written and verbal communication; you can explain trade-offs to engineers, executives, and bank stakeholders alike.

  • A bias for ownership and the ability to figure things out in messy, high-velocity environments.

Nice to have
  • Experience training, designing, or building production AI/ML systems, especially LLM agents or real-time voice (speech-to-text, text-to-speech, telephony).

  • Experience in fintech, banking, or other regulated industries (SOC 2, PCI, data privacy).

  • Previous startup or founder experience, ideally scaling a team from early stage through Series A/B.

The interview process

We respect your time. Our process is short and designed to show how you think and lead:

  1. 15-min call with our Talent Lead to learn more about the role

  2. 1-hour live coding session with a Founding Engineer

  3. 1-hour system design and technical leadership conversation with the CTO

  4. 1-day onsite with the team

Why join Kastle
  • Work with a world-class team building a generational AI company that will redefine how every loan in America is made and managed.

  • Move fast with real impact: add a feature in a few days and ship it to top 10 lenders the next week, reaching millions of customers.

  • Shape the engineering org: high ownership and direct input on architecture, team culture, and how engineering scales.

  • Competitive compensation plus meaningful equity at a high-growth company.

Skills Required

  • 7+ years building high-performance, real-time backend systems
  • 2+ years leading engineers as a tech lead, staff engineer, or engineering manager
  • Experience shipping large systems through a team
  • Primary experience with Python
  • Deep understanding of distributed systems, reliability, and fault tolerance
  • Excellent database design and performance optimization skills
  • Hands-on experience running production workloads on Kubernetes and cloud infrastructure
  • Clear written and verbal communication with engineers, executives, and bank stakeholders
  • Strong ownership and ability to work in messy, high-velocity environments
  • Experience training, designing, or building production AI/ML systems, especially LLM agents or real-time voice systems
  • Experience in fintech, banking, or other regulated industries
  • Previous startup or founder experience, ideally scaling a team from early stage through Series A/B
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The Company
768 Employees
Year Founded: 1972

What We Do

Kastle AI is an AI platform for consumer lending and servicing that provides an AI operating system to automate borrower interactions, ensure compliance, and reduce costs for mortgage lenders. Using AI voice agents, the platform integrates with existing contact centers and payment systems to modernize operations without disruption, managing high-volume phone calls from loan inquiry to payoff.

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