Infrastructure Engineer

Kastle•San Francisco, CA

9d•$180,000 - $275,000•Onsite

About The Position

Kastle is building an AI employee for financial services, using autonomous AI agents to support banks with payments, loan origination, and customer service. The company says it has processed more than $2 billion in transactions and is backed by Insight Partners and Y Combinator. The Infrastructure team builds the underlying systems used for major financial transactions. Kastle is seeking a Senior Infrastructure Engineer to design, build, and operate the distributed infrastructure powering AI agents in production at banks, lenders, and other financial institutions. The role focuses on consistency, fault tolerance, horizontal scalability, and low-latency coordination across cloud platforms, Kubernetes, and Terraform, while maintaining reliable, compliance-critical systems. This is an onsite position involving close collaboration with platform, ML, and security engineering.

Requirements

At least 5 years in infrastructure, platform, or backend engineering roles, with substantial hands-on distributed systems experience.
Strong understanding of distributed systems fundamentals, including consensus, replication, partitioning, consistency models (CAP/PACELC), and failure modes.
Production experience with at least one major cloud provider (AWS, GCP, or Azure) at scale.
Hands-on experience running Kubernetes in production, including cluster upgrades, networking, and security policy.
Experience designing or operating distributed data stores, message queues, or event streaming systems, such as Kafka, etcd, Cassandra, or CockroachDB.
Strong background in infrastructure-as-code, preferably Terraform, and CI/CD pipelines.
Proficiency in at least one programming or scripting language (Go, Python, or Rust) for building distributed tooling.
Experience owning production reliability, including on-call, incident response, and postmortems.
Comfort working onsite and collaborating closely with product, ML, and security teams.

Responsibilities

Design and operate distributed systems powering production AI agents, emphasizing consistency, fault tolerance, and horizontal scalability.
Architect service-to-service communication, coordination, and state management across multiple regions and availability zones.
Own Kubernetes cluster architecture, scaling, and security hardening across environments.
Build and maintain Terraform modules and GitOps pipelines for reviewed, versioned, repeatable infrastructure changes.
Design systems for regulated financial institutions’ reliability and auditability requirements, including replication, failover, backups, disaster recovery, and change logs.
Diagnose and resolve distributed-systems failure modes, including network partitions, cascading failures, split-brain scenarios, and race conditions.
Build observability through metrics, distributed tracing, logging, and alerting.
Partner with ML, platform, and security engineering on capacity planning, data consistency guarantees, and architecture reviews.
Participate in an on-call rotation for production infrastructure.
Mentor engineers on distributed systems design and review their architecture and infrastructure-as-code changes.