Infrastructure Engineer (AI for Financial Services)

An early-stage company is building an enterprise AI platform for financial institutions, working with sensitive data under tight security and compliance rules. It is hiring infrastructure engineers to design and protect the systems underneath the product, including customer environments that run inside the client’s own cloud.

Scope

• Design scalable infrastructure behind an AI knowledge engine that works over both structured feeds and unstructured internal documents
• Apply a security-first approach to private cloud deployments so data governance satisfies financial-services expectations
• Build dependable ingestion pipelines that combine public data with isolated, per-customer private data
• Set up monitoring and alerting for the bring-your-own-cloud deployment model
• Add permissions and audit logging so every AI answer can be traced back to its original sources
• Collaborate with the research and product groups to tune infrastructure for LLM serving, training and agent workloads
• Set up CI/CD and declarative infrastructure practices so releases ship fast, reliably and across several cloud vendors

Qualifications

• At least five years in platform or infrastructure engineering; staff-level experience is preferred
• Deep knowledge of one or more major clouds, together with containers and Kubernetes
• A security mindset and experience with data governance, particularly in regulated sectors
• Familiarity with monitoring and observability tooling (Datadog in use here)
• Understanding of compliance frameworks such as SOC, SOX and GDPR; financial regulation knowledge helps
• Startup instincts: moving quickly while still building robust systems
• Exposure to managed AI services like SageMaker or Bedrock

On-site in the San Francisco Bay Area or New York, NY. Visa sponsorship and transfers considered.