1 day ago
Kuwait City, KuwaitSenior
Responsibilities
- Own the AI behavior, agent systems, evaluations, and backend integration for production systems used by public-sector clients.
- Build production agents with reliable tool calling, guardrails, and observability.
- Design and adapt evaluations for client-specific risks and real-world outcomes.
- Apply context engineering, retrieval-augmented generation, model adaptation, and inference optimization where appropriate.
- Investigate production regressions, lead root-cause analysis, and implement preventative changes.
- Lead workstream planning and manage client scope, risk, and delivery expectations.
- Turn recurring client work into reusable tooling, evaluation components, and engineering guidance.
- 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 maintaining their reliability.
- Experience owning the AI behavior of a production system end to end.
- Experience designing evaluations that connect model behavior to real-world outcomes and detect regressions.
- Experience leading root-cause analysis on production AI or ML systems.
- Ability to work directly with clients and explain model behavior 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.
Categories
About Scale AI
Scale AI builds data annotation services and AI development tools for enterprises and government agencies, sold as a platform and managed services. Its products include the Scale Generative AI Platform for building and evaluating agents and the Data Engine for collecting, curating, and labeling training data, including RLHF and model evaluation. Founded in 2016 and headquartered in San Francisco, the company is privately held and works across domains from computer vision to LLM applications.