Field Engineer, AI Data Pipelines (TS/SCI)

Scale; Colorado Springs (CO); On-site; USD 181,000 - 227,000; Full time

Job summary

Scale is seeking a Field Engineer to work with federal AI projects and large public sector customers, building production-grade data pipelines and tooling. You will collaborate with Product, Engineering, and Operations to understand use cases and deliver practical solutions.

The role sits at the intersection of delivery, product, and engineering. The ideal candidate is a generalist software engineer who enjoys client work, solving ambiguous problems, and partnering across teams.

Qualifications

• Experience as a customer-facing engineer or in a similar hybrid role.
• Hands-on technical experience working with clients in a pre- or post-sales capacity.
• Development experience with Python, JavaScript, or other modern languages.
• A strong engineering background, ideally in computer science, mathematics, or another quantitative field.

Responsibilities

• Build end-to-end data integrations that sync customer data to Scale's platform.
• Work with customers' engineering teams to optimize data pipelines and API designs.
• Design and maintain playbooks, internal tools, documentation, and SDKs for long-term success.
• Partner with engineers and Operations to resolve blockers, debug delivery issues, and own escalations.
• Own the customer's technical experience throughout their time with Scale.
• Identify customer-specific feature requests with Account Executives and Product Managers.

Skills

Python

JavaScript

Customer-facing

Engineering fundamentals

Education

Computer science background

Tools

Kubernetes

Helm charts

CI/CD

APIs

Job description

Scale is seeking a Field Engineer to work with federal AI projects and large public sector customers, building production-grade data pipelines and tooling. You will collaborate with Product, Engineering, and Operations to understand use cases and deliver practical solutions.

The role sits at the intersection of delivery, product, and engineering. The ideal candidate is a generalist software engineer who enjoys client work, solving ambiguous problems, and partnering across teams.