Infrastructure Engineer

Description

About the Role

Help build and secure the infrastructure behind an enterprise AI data platform for financial services. You will work across cloud infrastructure, data systems, and AI workloads to support secure processing of sensitive information at scale.

Responsibilities

• Design scalable infrastructure for an AI knowledge platform handling structured and unstructured financial data.
• Build security-focused architecture for private cloud deployments and support data governance requirements.
• Develop ingestion pipelines for financial data feeds and internal documents.
• Create monitoring and alerting systems for customer-deployed infrastructure.
• Implement access controls and audit trails that trace AI interactions to their sources.
• Partner with AI research and product teams to optimize infrastructure for model inference, training, and agent workloads.
• Establish CI/CD and infrastructure-as-code practices for reliable deployments across multiple cloud providers.

Requirements

• Typically 5 to 10 years of infrastructure or platform engineering experience, with scope and progression aligned to a senior-level role.
• Experience with AWS, GCP, or Azure, plus containerization and Kubernetes at scale.
• Knowledge of data pipeline tooling and experience building or supporting complex ingestion systems.
• A security-minded approach and experience with data governance, ideally in regulated industries.
• Familiarity with observability tools such as Datadog and AI platforms such as SageMaker or Bedrock.
• Understanding of compliance requirements such as SOC, SOX, GDPR, or financial services regulations is a plus.
• Strong CS fundamentals and experience in an engineering-focused environment are valued.

Conditions

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

On-site in San Francisco, California.