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About the Role
Join an AI company building a secure data platform for financial services. You will build and operate infrastructure that supports large-scale data processing, AI workloads, and strict security and governance requirements.
Responsibilities
- Design scalable infrastructure for an AI platform processing structured and unstructured financial data.
- Build secure architecture for private cloud deployments and support data governance requirements in financial services.
- Develop data ingestion pipelines for external 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 source data.
- 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.
Requirements
- Typically 5 to 10 years of experience in cloud, infrastructure, or platform engineering, with scope appropriate for a senior-level role.
- Strong experience with at least one major cloud platform: AWS, GCP, or Azure, plus containerization and Kubernetes at scale.
- Experience building data pipelines or ingestion systems is useful.
- Security-minded approach and familiarity with data governance, regulated industries, or compliance requirements such as SOC, SOX, or GDPR.
- Knowledge of monitoring, logging, and observability tools, such as Datadog.
- Experience with AI platforms such as SageMaker or Bedrock is valuable.
- Strong infrastructure engineering fundamentals, a record of growing responsibility, and comfort working in an early-stage environment.
Skills
- AWS
- GCP
- Azure
- Kubernetes
- Datadog
- SageMaker
- Bedrock
- CI/CD
- Infrastructure-as-code
Location
- San Francisco, California
Work Type
- On-site
Experience Level
- Senior-level
Salary/Compensations
- $150,000 to $300,000 annually
Benefits
- Visa sponsorship is available.