Bretton AI
Software Engineer, Infrastructure
About this role
Bretton AI, a leading AI agent platform for financial services, seeks a Senior Infrastructure Engineer to design and operate secure, compliant Kubernetes-based systems serving major financial institutions. You'll own container-native infrastructure, progressive delivery pipelines, observability, and incident response while supporting SOC 2 compliance and enterprise customer deployments.
What you'll do
- Manage Kubernetes clusters, service meshes, and container security policies
- Design progressive delivery pipelines with canary deployments and automated rollbacks
- Build observability infrastructure in Datadog including dashboards, monitors, and distributed tracing
- Lead incident response for high-severity outages and capacity planning for AI inference
- Architect Infrastructure-as-Code solutions for VPCs, IAM, and on-premises deployments
- Support SOC 2 compliance controls and lead enterprise customer rollout engagements
What they're looking for
- Kubernetes and container orchestration (Docker, Helm, service mesh)
- AWS, GCP, or Azure cloud infrastructure at enterprise scale
- Infrastructure-as-Code (Terraform, Helm, Kustomize)
- Datadog or similar observability platforms
- Python programming
- Progressive delivery and safe deployment practices
- Incident response and capacity management
- Financial services compliance and regulated systems
Benefits
- Work on high-impact infrastructure serving billions of people
- Leadership opportunities mentoring mid-level engineers
- Direct customer engagement on enterprise deployments
- Infrastructure-focused role with product mindset
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
Bretton AI
Bretton AI builds an AI agent platform that automates compliance and regulatory operations for financial institutions. The company is hiring engineers across design, infrastructure, product, deployment, and solutions to develop and scale its compliance automation tools.
View all jobs at Bretton AILikely interview questions
- Walk us through a time you owned a Kubernetes cluster at scale—what were the biggest operational challenges, and how did you solve them?
- Describe your experience with progressive delivery and canary deployments. Have you had to roll back a production deployment, and what did you learn?