Infrastructure Engineer

The Role

We're looking for Infrastructure Engineers who will be instrumental in building and securing the backbone of our enterprise-grade AI data platform. You’ll design systems that handle large volumes of sensitive financial data under strict security and compliance requirements, including real-time correlation of public data with private, tenant-isolated customer data at scale.

What You'll Do

Design and build scalable infrastructure to support our AI-powered knowledge engine processing structured and unstructured financial data

Implement security-first architecture for private cloud deployments, ensuring data governance meets financial services requirements

Build robust data ingestion pipelines that handle everything from CapIQ feeds [structured data] to internal SharePoint documents [unstructured data]

Develop monitoring and alerting systems for our BYOC platform

Implement access controls and audit trails to ensure AI interactions are traceable back to primary sources

Partner with our AI Research and Product teams to optimize infrastructure for LLM inference and training workloads and building agent infrastructure

Establish CI/CD practices and infrastructure-as-code for rapid, reliable deployments orchestrated across multiple cloud providers

What You Have

3-10 years of experience in infrastructure or platform engineering

Strong background in cloud platforms (AWS, GCP, or Azure) with expertise in containerization and kubernetes

Security-minded approach with experience in data governance, especially in regulated industries

Experience with data pipeline technologies and real-time processing frameworks; most any ETL experience will do

Knowledge of modern monitoring, logging, and observability tools; we use Datadog

Understanding of compliance requirements (SOC, SOX, GDPR, financial services regulations is a plus)

Startup mentality with the ability to move fast while building robust, scalable systems

Experience with AI platforms like SageMaker or Bedrock