At a Glance
- Tasks: Lead the design and operation of AI systems for complex, unstructured documents.
- Company: Fully remote role with a focus on innovative AI solutions in healthcare and legal sectors.
- Benefits: Competitive salary, bonuses, private healthcare, and opportunities for professional growth.
- Why this job: Make a real impact by developing cutting-edge AI technology that transforms industries.
- Qualifications: Experience with LLMs, NLP, and working in regulated environments is essential.
- Other info: Join a dynamic team with excellent career progression and mentorship opportunities.
The predicted salary is between 84000 - 116000 £ per year.
Fully remote (UK based only)
£100,000 plus + bonus + private healthcare
Permanent - Full-time employment
This role is for an experienced AI Engineer with proven production experience building LLM-based systems for long, noisy and highly regulated text documentation, ideally in highly regulated domains.
You will take technical ownership of NLP and LLM systems already in live use within a medico-legal platform. The focus is on designing, building, evaluating and operating AI systems that work reliably on complex, unstructured documents, not research prototypes or prompt-only solutions. You will remain hands-on across the full lifecycle, from problem framing and model design through to deployment, monitoring and iteration in production.
The role
You will lead the design and operation of LLM driven systems used to process large volumes of long-form, unstructured and inconsistent text common to healthcare and legal workflows. The work requires strong judgement around accuracy, auditability, explainability and regulatory constraints. You will act as the technical lead for AI delivery, working closely with MLOps and Data Engineering teams and mentoring junior AI engineers.
Key responsibilities
- Design, build and operate LLM-based systems for long, noisy and highly regulated text documentation. (Text Classification, Text Summarisation)
- Own end-to-end delivery of NLP and LLM solutions from concept through to production
- Build and optimise retrieval-augmented generation (RAG) pipelines over large document sets
- Make clear technical trade-offs between fine-tuning, prompting and retrieval approaches
- Build and maintain robust evaluation frameworks for accuracy, quality and reliability
- Monitor model behaviour, performance and drift in live environments
- Work with MLOps to deploy, retrain and version models using production-grade pipelines
- Ensure explainability, auditability and responsible AI practices are embedded by design
- Set technical standards and mentor junior engineers across the AI team
Required experience
- Demonstrable experience building LLM-based systems for long, noisy, document-heavy data in production
- Strong hands-on experience with NLP and LLMs, including transformers, fine-tuning and RAG
- Proven experience working with highly unstructured text in regulated or compliance-heavy environments
- Experience designing and running model evaluation and monitoring in production
- Clear understanding of explainability, auditability and governance for AI systems
- Strong understanding of MLOps practices, CI/CD pipelines and model versioning
- Experience in regulated domains is strongly preferred
Career progression
This role is the technical lead for the AI function, with ownership of delivery quality, standards and mentoring. As the team grows, scope can expand into broader technical leadership while remaining hands-on.
Artificial Intelligence Engineer in Manchester employer: Innova Recruitment
Contact Detail:
Innova Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech community, attend meetups or webinars, and don’t be shy about sliding into DMs. Building connections can lead to job opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and NLP. Having tangible examples of your work can really set you apart when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common AI and NLP questions. Think about how you’d explain complex concepts simply, as you might need to demonstrate your understanding of explainability and auditability in AI systems.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Artificial Intelligence Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of an AI Engineer. Highlight your experience with LLM-based systems and any work you've done in regulated environments. We want to see how your skills match up with what we're looking for!
Showcase Your Projects: Include specific projects where you've designed, built, or operated NLP and LLM systems. We love seeing real-world applications of your skills, so don’t hold back on the details that show off your hands-on experience!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Explain why you're passionate about AI and how your background makes you a perfect fit for our team. We want to feel your enthusiasm and see your personality come through!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re keen on joining the StudySmarter family!
How to prepare for a job interview at Innova Recruitment
✨Know Your Stuff
Make sure you brush up on your knowledge of LLM-based systems and NLP. Be ready to discuss your hands-on experience with transformers, fine-tuning, and RAG pipelines. The more specific examples you can provide from your past work, the better!
✨Understand the Domain
Since this role involves working in highly regulated environments, it’s crucial to demonstrate your understanding of compliance and governance in AI. Familiarise yourself with the challenges of processing unstructured text in healthcare and legal workflows.
✨Showcase Your Problem-Solving Skills
Be prepared to talk about how you've tackled complex problems in previous projects. Highlight your approach to model evaluation, monitoring, and ensuring explainability and auditability in your AI systems. Real-world examples will make your case stronger!
✨Engage with the Team
This role involves mentoring junior engineers and collaborating with MLOps and Data Engineering teams. Show your enthusiasm for teamwork and leadership by discussing how you've supported others in your previous roles and how you plan to contribute to the team dynamic.