Field Engineer, Public Sector

Field Engineer, Public Sector at Scale AI

Scale AI is at the forefront of powering AI-enabled technologies, from autonomous driving to drones, robotics, and large language models, collaborating with leading self-driving car and generative AI companies.

As a Field Engineer, Public Sector, you will be instrumental in our federal AI projects, directly impacting revenue by ensuring our largest public sector customers have seamless experiences and become long-term partners. You will work closely with customers to build production-grade data pipelines, understanding their use-cases thoroughly to create necessary tooling and documentation for scalable growth.

Field Engineers are experts in Scale's products and codebase, possessing strong technical knowledge in web development, API usage, and large-volume data handling. This role requires excellent relationship-building and project management skills, combined with a collaborative spirit.

The ideal candidate is a software engineer generalist who thrives on direct client interaction, transforming ambiguous requirements into sustainable solutions in partnership with Product and Engineering teams. This role offers a unique blend of customer delivery, product development, and engineering, leveraging both your technical and interpersonal strengths.

What you will do:

• Implement end-to-end data integrations, syncing customer data to Scale’s platform and back.
• Work closely with customer engineering teams to optimize data pipelines, providing input for API endpoint design and input/output schemas.
• Design, develop, and maintain playbooks, internal tools, Scale’s documentation, and SDKs for quick customer setup and long-term success.
• Partner with Software Engineers and Operations to resolve technical hurdles and own technical escalations from customers.
• Be accountable for the customer’s technical experience throughout their engagement with Scale.
• Collaborate with Account Executives and Product Managers to identify customer-specific feature requests.
• Develop technical domain expertise in areas like Large Language Models, 2D Image Annotation, and API integrations.
• Evangelize Scale and interact with customers at major events.
• Maintain an active TS/SCI clearance.

Ideally you'd have:

• A proven track record as a hybrid customer-facing engineer or similar role, demonstrating versatility.
• Prior hands-on technical experience with clients in pre- or post-sales capacities to achieve business goals.
• Previous experience developing with Python and JavaScript, or other modern software languages.
• A strong engineering background, preferably in Computer Science, Mathematics, or other quantitative fields.
• Strong project management and interpersonal skills.
• Effective presentation skills with high technical credibility when engaging with executives and engineers.
• High comfort level communicating effectively across internal and external organizations.
• Intellectual curiosity, empathy, and the ability to operate with high velocity.

Nice to haves:

• Experience in AI.
• Experience working in classified environments.
• Previous experience as a technical go-to-market resource.
• Understanding of DevSecOps principles, including secure software delivery, infrastructure as code, and continuous integration/deployment.
• Hands-on knowledge of container orchestration with Kubernetes and experience with Helm charts.
• Experience automating infrastructure and configuration management using Ansible or similar tools.

About Scale AI:

Scale AI's mission is to develop reliable AI systems for the world's most important decisions. Our products provide high-quality data and full-stack technologies that power leading models, helping enterprises and governments build, deploy, and oversee AI applications with real impact. We partner with industry leaders like Meta, Cisco, and U.S. government agencies. We are committed to an inclusive and equal opportunity workplace.

Key skills/competency:

• Data Integration
• API Development
• Python Programming
• JavaScript Development
• Project Management
• Client Relationship Management
• Large Language Models (LLMs)
• AI/Machine Learning
• DevSecOps Principles
• Kubernetes Orchestration