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Home/Jobs in Kuwait/Technology Jobs/Senior Applied AI Engineer
Scale AI logo
Scale AI

Senior Applied AI Engineer

🇰🇼 Kuwait City, Kuwait🏢 On-site
AIMachine LearningBackend EngineeringRAGLLMsPythonProduction AI

At a Glance

Category
💻 Technology
Level
Senior
Type
Full-time
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Scale AI

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.

What you'll do

  • 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 where the use case requires them
  • Apply context engineering, retrieval-augmented generation, model adaptation, or inference optimisation where the use case calls for them
  • 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

What we look for

  • Backend engineering experience, with a track record of taking AI/ML systems into production and keeping them reliable
  • Experience owning the AI behaviour of a production system end to end, rather than delivering a component scoped by another team
  • Experience designing evaluations that tie model behaviour to real-world outcomes, and using them to catch regressions
  • Experience leading root-cause analysis on a production AI or ML system
  • Comfort working directly with clients, including explaining model behaviour and trade-offs to non-technical stakeholders
  • Experience handling regulated or sensitive data and designing for auditability; sovereign or on-premise deployment experience is valuable

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.

About Us:

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 are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.

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

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Requirements

  • •Backend engineering experience with a track record of taking AI/ML systems into production
  • •Experience owning the AI behavior of a production system end to end
  • •Experience designing evaluations that tie model behavior to real-world outcomes
  • •Experience leading root-cause analysis on production AI or ML systems
  • •Comfort working directly with clients and explaining model behavior to non-technical stakeholders
  • •Experience handling regulated or sensitive data and designing for auditability

Nice to Have

  • •Sovereign or on-premise deployment experience

Responsibilities

  • •Own the AI layer of production systems, including agents, model integration, and backend services
  • •Build production agents with reliable tool calling, guardrails, and observability
  • •Select and adapt evaluation methods and design new evaluations for client-specific risks
  • •Apply context engineering, retrieval-augmented generation, model adaptation, or inference optimization
  • •Investigate regressions, lead root-cause analysis, and implement preventative changes
  • •Lead project planning for workstreams and manage client expectations on scope and risk
  • •Codify recurring client work into reusable tooling and guidance
  • •Mentor engineers through code review, pairing, and delegated ownership
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Scale AI provides a data labeling platform to help build AI models. It serves companies developing machine learning and artificial intelligence applications.

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