About the Role

Join the infrastructure team at a fintech company building an enterprise AI data platform. You will help create secure, scalable systems for processing sensitive financial information and connecting public data with private, tenant-isolated customer data.

What You'll Do

Design and build infrastructure for an AI knowledge platform processing structured and unstructured financial data.

Develop security-first architectures for private cloud deployments and support data governance requirements.

Build ingestion pipelines for financial data feeds and internal document sources.

Create monitoring and alerting for customer-managed cloud deployments.

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

Partner with AI research and product teams to support 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, cloud, or data infrastructure engineering, with scope and progression aligned to a senior-level role.

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

Experience with containers and Kubernetes at scale; familiarity with data pipeline tooling is useful.

Knowledge of observability tools such as Datadog and experience supporting reliable production systems.

A security-minded approach, ideally with experience in regulated industries and familiarity with SOC, SOX, GDPR, or financial services requirements.

Experience with AI infrastructure platforms such as SageMaker or Bedrock is valuable.

Strong computer science fundamentals and experience in a high-performing engineering environment.

Compensation & Benefits

Base salary: $150,000 to $300,000 annually. Visa sponsorship is available. Equity details were not provided.

Location

On-site in San Francisco, California.