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Artificial Intelligence Engineer

Digital Waffle
Department:Data Engineer
Type:REMOTE
Region:UK
Location:London Area, United Kingdom
Experience:Mid-Senior level
Salary:£70,000 - £100,000
Skills:
NLPLLMSTRANSFORMERSFINE-TUNINGRAGAGENTSMLOPSCI/CDDOCKERKUBERNETESAZURE MLDEVOPS
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Job Description

Posted on: February 20, 2026

Senior AI Engineer (NLP / LLMs) – remote (UK based)£70-100k depending on experience

A high-growth SaaS company is hiring a Senior AI Engineer to help build intelligent, mission-critical systems used in highly regulated environments.

The platform applies machine learning and large language models across complex, end-to-end data workflows, solving real-world problems with measurable social impact.

The Role

As a Senior AI Engineer, you’ll design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business and regulatory requirements into scalable, reliable AI systems. This is a hands-on role for someone who enjoys owning outcomes, balancing experimentation with real-world delivery.

What You’ll Be Doing

  • Designing and developing NLP and LLM-driven solutions for complex, real-world use cases
  • Fine-tuning and adapting foundation models using domain-specific data
  • Building evaluation frameworks, prompt testing tools and data preprocessing pipelines
  • Monitoring, optimising and maintaining deployed models for performance, cost and reliability
  • Implementing explainability, fairness and bias-mitigation strategies
  • Collaborating on MLOps pipelines, CI/CD workflows and production deployments
  • Mentoring junior engineers and promoting best practices across the team
  • Staying current with advances in AI, NLP and MLOps to drive continuous improvement

What We’re Looking For

  • Proven experience as an AI or Machine Learning Engineer with end-to-end model ownership
  • Strong expertise in NLP and LLMs (transformers, fine-tuning, RAG, agents)
  • Experience translating research and experimentation into production systems
  • Solid understanding of MLOps, including CI/CD, monitoring and model lifecycle management
  • Hands-on experience with Docker and Kubernetes
  • Strong communication skills and experience mentoring or leading others

Nice to Have

  • Experience working in regulated or sensitive domains
  • Exposure to graph-based retrieval techniques
  • Experience with Azure ML and DevOps integrations
Originally posted on LinkedIn

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