Senior AI Engineer, Production LLMs & Guardrails (Hybrid)

Oliver Bernard

Greater London

Hybride

GBP 90 000 - 130 000

Plein temps

Il y a 8 heures
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Résumé du poste

Oliver Bernard in London is seeking a Senior Applied AI Engineer to join our hybrid work setup. You will own AI engagements end-to-end, delivering production-grade AI solutions, including LLMs, pipelines, agents and workflows, aligned with an ambitious AI roadmap.

You will collaborate closely with Data Science, Decisioning, Engineering and non-technical stakeholders to deploy AI components into live customer-facing environments, optimise costs and ensure robust evals and guardrails.

Qualifications

  • Proven experience shipping LLM-powered systems into production.
  • Hands-on experience with LLM APIs, agents, orchestration, tool use, structured outputs and RAG.
  • Strong understanding of LLM evaluation, regression testing and quality measurement.
  • Experience implementing AI safety and guardrails, including PII, prompt injection and human-in-the-loop approaches.

Responsabilités

  • Own AI engagements end-to-end, from identifying the problem through to production and handover.
  • Build production-grade AI solutions, including LLMs, pipelines, agents and workflows.
  • Develop and implement evals, guardrails, monitoring and cost/accuracy optimisation.
  • Deploy ML and AI components into live customer-facing environments.
  • Work closely with Data Science, Decisioning, Engineering and non-technical stakeholders.

Connaissances

LLM-powered systems
LLM APIs
AI safety
RAG
Evaluation

Description du poste

Oliver Bernard in London is seeking a Senior Applied AI Engineer to join our hybrid work setup. You will own AI engagements end-to-end, delivering production-grade AI solutions, including LLMs, pipelines, agents and workflows, aligned with an ambitious AI roadmap.

You will collaborate closely with Data Science, Decisioning, Engineering and non-technical stakeholders to deploy AI components into live customer-facing environments, optimise costs and ensure robust evals and guardrails.

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