Field Engineer, Data Engine (AI)

TL;DR

Field Engineer, Data Engine (AI): Developing and deploying data integrations, pipelines, agents, and reliable backend systems for government customers with an accent on customer-site solutions, cloud-native infrastructure, and secure system integration. Focus on building end-to-end data flows, deploying software in secured environments, and solving complex integration challenges across customer workflows.

Location: St. Louis, Missouri, or Washington, DC; hybrid setup with more than 50% onsite work in a secured space. The role requires an active Secret clearance and willingness to obtain a TS/SCI clearance.

Salary: $140,000–$220,000 USD for St. Louis; $170,000–$260,000 USD for Washington, DC.

Company

Scale AI develops reliable AI systems, high-quality training data, and full-stack technologies for enterprises and government agencies.

What you will do

• Define and execute data pipeline and agent solutions with cross-functional teams.
• Implement end-to-end integrations that synchronize customer data with the platform.
• Deploy and maintain software at customer sites.
• Develop customer-requested features and support successful customer engagements.
• Build robust backend systems that can operate as standalone products.
• Work directly with stakeholders to understand requirements and deliver secure, innovative solutions.

Requirements

• Experience with ETL, data pipelines, data modeling, data warehousing, and data governance.
• Background as a customer-facing, forward-deployed, or hybrid software engineer.
• Professional experience developing with Python.
• Knowledge of cloud platforms and cloud-native application development.
• Understanding of Linux, shell scripting, operating systems, and networking fundamentals.
• Active Secret clearance and willingness to obtain TS/SCI clearance.

Nice to have

• Experience with Docker and Kubernetes.
• Knowledge of networking configuration, including ports and protocols.

Culture & Benefits

• Comprehensive health, dental, and vision coverage.
• Retirement benefits and generous paid time off.
• Learning and development stipend.
• Equity compensation may be available for eligible roles.
• Commuter stipend may be available.
• Inclusive equal opportunity workplace with reasonable accommodation support.