Senior Applied AI Engineer - Production AI & Client Impact

Scale AI; Greater London; On-site; GBP 120,000 - 150,000; Full time

Job summary

Scale AI is seeking a Senior Applied AI Engineer to own the AI behaviour of production systems for public sector clients, including agents, evaluations, and backend integration. You will lead delivery for your workstream and serve as the technical contact on how AI performs on live data.

You will guide design of evaluations, tool calling, observability, and model adaptation while mentoring other engineers and collaborating with clients to align outcomes with risks and requirements.

Qualifications

• Proven backend engineering experience delivering AI/ML in production.
• Experience owning AI behavior of production systems end to end.
• Hands-on evaluation design tied to real-world outcomes.

Responsibilities

• Own the AI layer of production systems for public-sector clients, including agents, model integration, and backend services.
• Build production agents with reliable tool calling, guardrails, and observability.
• Design evaluations for client-specific risks and monitor model performance on live data.
• Apply context engineering, retrieval-augmented generation, and inference optimization.
• Lead root-cause analysis on regressions and implement preventative changes.
• Plan workstreams and manage client expectations on scope, risk, and delivery.
• Codify recurring work into reusable tooling and guidance for engineers.
• Mentor engineers through code reviews and paired programming.

Skills

Backend engineering

Production systems

AI/ML in production

Client communication

Root-cause analysis

On-premise deployment

Mentoring

Job description

Scale AI is seeking a Senior Applied AI Engineer to own the AI behaviour of production systems for public sector clients, including agents, evaluations, and backend integration. You will lead delivery for your workstream and serve as the technical contact on how AI performs on live data.

You will guide design of evaluations, tool calling, observability, and model adaptation while mentoring other engineers and collaborating with clients to align outcomes with risks and requirements.