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3 дня назад

Forward Deployed AI Engineer

70 000 - 100 000GBP
Формат работы
remote (только United_kingdom)/hybrid
Тип работы
fulltime
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Forward Deployed AI Engineer (RAG/LLM): Building and deploying production AI solutions for clients, from discovery and architecture through MVP and production, with an accent on RAG, AI agents, LLM integrations, MCP, and enterprise environments. Focus on designing evaluation and testing frameworks, implementing security, scalability, guardrails and observability, and converting successful solutions into reusable platform accelerators.

Location: Hybrid Leeds, United Kingdom, with remote flexibility

Salary: £70,000–£100,000 per annum

Company

hirify.global is a growing technology consultancy building an AI-native engineering capability and delivering AI solutions for clients.

What you will do

  • Build AI solutions using RAG, AI agents, LLM integrations and MCP.
  • Take solutions from prototype through production, including security, scalability, guardrails and observability.
  • Build AI evaluation and testing frameworks to measure accuracy and reliability.
  • Work with complex client data, integrations and enterprise environments.
  • Collaborate directly with clients, demonstrate progress and iterate based on feedback.
  • Develop the internal AI platform, reusable engineering accelerators and client engineering capability.

Requirements

  • Strong software engineering fundamentals covering clean code, testing, CI/CD and production systems.
  • Strong programming skills in Python, TypeScript or similar, with experience across multiple modern languages.
  • Full-stack capability, including backend and data engineering.
  • Experience building and shipping production LLM or AI applications.
  • Hands-on experience with RAG, AI agents, prompt engineering, tool orchestration, MCP, AI evaluation, datasets and guardrails.
  • Client-facing experience and an understanding of enterprise security, compliance and legacy environments, combined with strong autonomy and communication skills.

Nice to have

  • Experience with vector databases, embeddings or fine-tuning.
  • AWS or Google Cloud experience.
  • Startup or founder experience.
  • Open-source contributions or AI side projects.

Culture & Benefits

  • Hybrid working model with remote flexibility.
  • Private healthcare.
  • Professional development and funded learning.
  • Opportunity to work on modern AI-enabled systems at scale.
  • Clear progression within a growing engineering function.

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