About the Role

Join an AI company building an enterprise data platform for financial services. You will help create and secure the infrastructure that processes sensitive structured and unstructured data while supporting reliable AI workloads.

What You'll Do

Design scalable infrastructure for an AI-powered platform handling structured and unstructured financial data.

Build security-focused architecture for private cloud deployments and support data governance requirements.

Develop robust ingestion pipelines for financial feeds and internal business documents.

Create monitoring and alerting systems for customer-managed cloud deployments.

Implement access controls and audit trails that connect AI interactions to their source materials.

Partner with AI research and product teams to optimize infrastructure for LLM inference, training, and agent workloads.

Establish CI/CD and infrastructure-as-code practices for reliable deployments across cloud providers.

What We're Looking For

Typically 5 to 10 years of experience in infrastructure, platform, or data infrastructure engineering.

Strong expertise in at least one major cloud platform: AWS, GCP, or Azure.

Experience with containerization and Kubernetes at scale, plus data pipeline tooling.

Familiarity with monitoring, logging, and observability tools such as Datadog.

Security-minded experience with data governance, ideally in regulated industries.

Understanding of compliance frameworks such as SOC, SOX, GDPR, or financial services regulations.

Experience with AI platforms such as SageMaker or Bedrock is useful.

Strong infrastructure engineering foundations, a record of increasing scope, and interest in early-stage environments.

Compensation & Benefits

Base salary: $150,000 to $300,000 annually. Visa sponsorship is available.

Location

On-site in San Francisco, California.