Senior Applied AI Engineer

Description

About the role

Scale's Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. As a Senior Applied AI Engineer, you'll own the AI behaviour of production systems our clients depend on, including the agents, evaluations, and backend integration behind them. You'll lead delivery for your workstream and act as the technical point of contact for clients on how their AI performs on live data.

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We comply with the United States Department of Labor's Pay Transparency provision .

Responsibilities

• Own the AI layer of production systems for public sector clients, including agents, model integration, and the backend services they run on
• Build production agents from established architectural patterns, with reliable tool calling, guardrails, and observability
• Select and adapt established evaluation methods, and design new evaluations for client-specific risks
• Apply context engineering, retrieval-augmented generation, model adaptation, or inference optimisation
• Investigate regressions in the systems you own, lead root-cause analysis, and implement preventative changes
• Lead project planning for your workstream and manage client expectations on scope, risk, and delivery
• Codify recurring client work into reusable tooling, evaluation components, or guidance that other engineers adopt
• Mentor engineers through code review, pairing, and delegated ownership

Requirements

• Backend engineering experience, with a track record of taking AI/ML systems into production and keeping them reliable
• Ownership of the AI behaviour of a production system end to end, rather than delivering a component scoped by another team
• Hands-on evaluation design that ties model behaviour to real-world outcomes, used to catch regressions
• Comfort working directly with clients, including explaining model behaviour and trade-offs to non-technical stakeholders
• Practical knowledge of handling regulated or sensitive data and designing for auditability; sovereign or on-premise deployment experience is valuable
• Experience leading root-cause analysis on production AI or ML systems
• Where this role sits
• Your primary accountability covers production AI behaviour, its backend integration, and the evaluation required for a specific customer. Senior Full-Stack Engineers own the complete user-facing application and its infrastructure. ML Research Engineers lead novel agent architecture and the benchmark methodology used across accounts. The roles work together on agents and evaluation, with accountability set by the scope of the problem.
• PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.