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- Tasks: Lead AI projects, manage a small team, and enhance system design.
- Company: Join a pioneering UK healthtech company transforming healthcare with AI.
- Benefits: Enjoy hybrid work, competitive salary, and opportunities for professional growth.
- Why this job: Be at the forefront of AI innovation in healthcare while mentoring others.
- Qualifications: Strong Python skills and experience with NLP, REST APIs, and cloud technologies required.
- Other info: This is a permanent role with a structured interview process.
The predicted salary is between 68000 - 72000 £ per year.
Location: Oxford/London (Hybrid – 2 days per week in office)
Type: Permanent
Salary: £85,000–£90,000
Interview Process: 3 stages
We're working with a UK-based healthtech company looking for a Lead AI Engineer. This role sits within a cross-functional Data & AI team, focused on taking NLP projects into production and improving system design and infrastructure. You’ll also guide a small technical team (2–3 people), but the focus remains deeply technical - ideal for someone from a software engineering background.
What you'll do:
- Build and scale NLP/document processing pipelines using microservices
- Lead 2–3 reports (data scientists + AIOps engineer)
- Set engineering standards and lead architecture, code reviews, and deployment
- Work with DevOps, product, and data teams to deliver production-ready solutions
What you'll need:
- Strong Python and experience with PyTorch or TensorFlow
- Solid understanding of REST APIs, CI/CD, Docker, Kubernetes, and AWS
- Proven delivery of NLP/OCR projects with unstructured data
- Experience managing or mentoring engineers
Bonus points for:
- Experience in regulated domains
- Knowledge of semantic search, graph/vector databases
- Java or C# background and understanding of SOLID principles
Interested? Message me here or email mmatysik@trg-uk.com
Lead AI Engineer employer: trg.recruitment
Contact Detail:
trg.recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in NLP and AI technologies. Being well-versed in current advancements will not only boost your confidence during discussions but also demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the healthtech sector, especially those working on AI projects. Attend relevant meetups or webinars to connect with potential colleagues and learn about their experiences.
✨Tip Number 3
Prepare to discuss your previous projects in detail, particularly those involving NLP and unstructured data. Be ready to explain your role, the challenges you faced, and how you overcame them.
✨Tip Number 4
Showcase your leadership skills by discussing any mentoring or team management experiences. Highlight how you've guided teams through technical challenges and contributed to their professional growth.
We think you need these skills to ace Lead AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, PyTorch or TensorFlow, and any relevant NLP projects. Emphasise your technical skills and leadership experience, especially in managing small teams.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about AI and healthtech. Mention specific projects you've worked on that relate to the job description, particularly those involving unstructured data and microservices.
Showcase Relevant Projects: If you have a portfolio or GitHub repository, include links to projects that demonstrate your expertise in NLP, REST APIs, and cloud technologies like AWS. This will give the hiring team a clear view of your capabilities.
Prepare for Technical Questions: Anticipate technical questions related to your experience with CI/CD, Docker, Kubernetes, and your approach to system design. Be ready to discuss how you've led engineering standards and code reviews in previous roles.
How to prepare for a job interview at trg.recruitment
✨Showcase Your Technical Skills
As a Lead AI Engineer, you'll need to demonstrate your strong Python skills and experience with frameworks like PyTorch or TensorFlow. Be prepared to discuss specific projects where you've successfully implemented NLP solutions, focusing on the challenges you faced and how you overcame them.
✨Prepare for System Design Questions
Expect questions about system design and architecture, especially related to microservices and deployment strategies. Brush up on your knowledge of REST APIs, CI/CD processes, and containerisation tools like Docker and Kubernetes, as these are crucial for the role.
✨Highlight Leadership Experience
Since you'll be guiding a small technical team, it's important to highlight any previous leadership or mentoring experiences. Share examples of how you've supported team members in their development and how you've set engineering standards in past roles.
✨Understand the Company’s Domain
Familiarise yourself with the healthtech industry and any relevant regulations. If you have experience in regulated domains, make sure to mention it, as this could give you an edge. Understanding the context in which your AI solutions will operate is key to demonstrating your fit for the role.
