Senior Cloud Services Engineer (Identity and Fraud, AI/ML)

Equifax • Boise, ID

13d

About The Position

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you. As a Cloud Engineer on the USIS Data & Analytics Team in Boise, you will be responsible for partnering with your teammates to develop the strategy/design of services the team owns in our cloud environments (AWS/GCP) incorporating industry best practices and in collaboration with internal and/or external stakeholders. In addition, you will work with teams across Equifax to enable our products by bringing solutions to market serving our internal and external customers. What you’ll do: Execute strategy, design, implementation, operation, and continual improvement of the team’s products and services, and their associated infrastructure. Provide guidance through enabling the Machine Learning Engineers and Data Scientists to perform their job duties in the most secure, efficient, innovative, and cost-effective way as possible. Implement secure and scalable solutions in our cloud environments (AWS/GCP) that meet the needs of our internal and external customers. This includes partnering with other EFX Teams to implement what’s required. Build CI/CD pipelines to deploy infrastructure and application changes to multiple environments and regions. Manage data pipelines, including designing, implementing, and operating multiple data pipelines with other internal teams. Define all cloud resources using Terraform. Troubleshoot and resolve issues across services deployed to environments in our cloud environments (AWS/GCP). Participate in relevant role-based guilds across Equifax. Participate in the team’s on-call rotation.

Requirements

• BS degree in a STEM major or equivalent job experience required; Master’s Degree preferred; AI/ML coursework preferred
• 7+ years of related work experience, preferrably in-depth experience with AWS and GCP.
• Experience supporting AI/ML platforms and services, including infrastructure for model training, deployment, and inference.
• Experience with MLOps frameworks and tools for model versioning, experiment tracking, and workflow automation (e.g., MLFlow, Kubeflow, AWS Step Functions).
• Proven experience in technical leadership and mentorship, with the ability to influence strategy and partner between EFX teams.
• In-depth experience with containerization (Docker), container orchestration systems, specifically Kubernetes (e.g., EKS, GKE), and service mesh solutions (e.g., Istio).
• Expertise with Infrastructure as Code (IaC), primarily using Terraform to define and manage cloud resources.
• Experience with metrics, monitoring, and visualization tools such as Grafana or DataDog.
• Experience with network design and operations in a production environment.
• Excellent written and communication skills.
• Ability to take vague requirements, develop a plan, and execute it with first-time quality while keeping it simple and compliant.

Nice To Haves

• Experience with model serving patterns for deploying models with scalable, low-latency microservices on Kubernetes.
• Experience with build automation systems such as GitLab CI.
• Scripting or programming experience.
• Desire to automate where it makes sense and is possible.
• Deep experience with Terraform, including extensive terraform module development experience at scale.
• Experience with network/server configuration for automated software deployment.
• Experience in the Financial Industry or Ecommerce.
• Familiarity with Snowflake, including running queries for validation and supporting application-level integrations.
• Experience with Golang or Python.
• Experience with integration of APM solutions such as DataDog.
• Experience with Linux administration and troubleshooting.

Responsibilities

• Execute strategy, design, implementation, operation, and continual improvement of the team’s products and services, and their associated infrastructure.
• Provide guidance through enabling the Machine Learning Engineers and Data Scientists to perform their job duties in the most secure, efficient, innovative, and cost-effective way as possible.
• Implement secure and scalable solutions in our cloud environments (AWS/GCP) that meet the needs of our internal and external customers. This includes partnering with other EFX Teams to implement what’s required.
• Build CI/CD pipelines to deploy infrastructure and application changes to multiple environments and regions.
• Manage data pipelines, including designing, implementing, and operating multiple data pipelines with other internal teams.
• Define all cloud resources using Terraform.
• Troubleshoot and resolve issues across services deployed to environments in our cloud environments (AWS/GCP).
• Participate in relevant role-based guilds across Equifax.
• Participate in the team’s on-call rotation.

Benefits

• comprehensive compensation and healthcare packages
• 401k matching
• paid time off
• organizational growth potential through our online learning platform with guided career tracks

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees