Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deploy AI systems that tackle real-world healthcare challenges.
- Company: Fast-growing life sciences tech company focused on innovative AI solutions.
- Benefits: Hybrid working, career growth, health insurance, and access to cutting-edge AI tools.
- Why this job: Make a tangible impact in healthcare while working with advanced AI technologies.
- Qualifications: 3+ years in AI or data science, strong Python skills, and experience with LLM APIs.
- Other info: Collaborative culture with a focus on innovation and professional development.
The predicted salary is between 36000 - 60000 £ per year.
We're looking for AI engineers who want to build production-ready AI solutions that tackle real-world challenges in life sciences, from RAG chatbots to agentic AI systems supporting evidence-driven projects. You will design, develop, and deploy AI systems that have measurable impact, influence patient access to treatments, and support decision-making in healthcare.
Our client is a fast-growing life sciences technology company with offices in the UK and Europe. They specialise in applying AI to accelerate patient access to treatments through practical, evidence-driven solutions. The company values collaboration, innovation, and creating a culture where employees can grow and make a tangible impact in healthcare.
Key responsibilities- Design, develop, and deploy AI systems with a focus on RAG chatbots and agentic AI.
- Lead real-world evidence projects, ensuring AI solutions are reliable, measurable, and impactful.
- Implement data pipelines, retraining workflows, and monitoring to maintain model performance.
- Design evaluation metrics to assess accuracy, latency, UX quality, safety, and real-world utility.
- Collaborate with product, software, and platform teams to deliver scalable, production-ready AI solutions.
- Champion software engineering best practices, including code reviews, testing, CI/CD, and reproducibility.
- Ensure AI solutions meet security, compliance, and responsible AI standards.
- Mid-to-senior AI engineer with 3+ years in data science or software engineering, including substantial AI experience.
- Strong Python skills and experience with LLM APIs (OpenAI, Anthropic, or similar).
- Expertise in GenAI frameworks (LangChain, LlamaIndex, Haystack, Hugging Face Transformers).
- Hands-on experience with RAG pipelines, vector databases (Pinecone, FAISS, Weaviate), and chatbot deployment.
- Proven experience with agentic AI (tool use, planning, multi-step reasoning) and production-level systems.
- Experience delivering AI solutions in real-world or evidence-driven projects, preferably in life sciences.
- Strong communication skills and understanding of AI ethics, bias mitigation, and responsible AI practices.
- Model fine-tuning, knowledge graphs, or multi-modal AI systems.
- AWS or other cloud platform experience for scalable GenAI deployment.
- Client-facing experience in AI projects.
- Hybrid working model (UK & Europe).
- Career development and professional growth opportunities.
- Collaborative culture with a focus on impact and innovation.
- Health insurance and wellness programmes.
- Access to cutting-edge AI tools and projects.
Artificial Intelligence Engineer in London employer: Aspire Life Sciences Search
Contact Detail:
Aspire Life Sciences Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in London
✨Tip Number 1
Network like a pro! Get out there and connect with people in the AI and life sciences space. Attend meetups, webinars, or industry events to meet potential employers and fellow engineers. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those related to RAG chatbots or agentic AI systems. Having tangible examples of your work can really set you apart when chatting with recruiters or during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and familiarising yourself with LLM APIs and GenAI frameworks. Practice coding challenges and be ready to discuss your experience with real-world evidence projects – it’s all about demonstrating your expertise!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting opportunities in AI and life sciences waiting for you. Plus, applying directly can sometimes give you an edge over other candidates. Let’s get you that dream job!
We think you need these skills to ace Artificial Intelligence Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the AI Engineer role. Highlight your experience with RAG chatbots, agentic AI, and any relevant projects in life sciences. We want to see how your skills align with our mission!
Showcase Your Skills: Don’t just list your skills; demonstrate them! Include specific examples of how you've used Python, LLM APIs, or GenAI frameworks in past projects. We love seeing real-world applications of your expertise.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to describe your experiences and achievements. We appreciate a well-structured application that makes it easy for us to see your potential.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Aspire Life Sciences Search
✨Know Your AI Stuff
Make sure you brush up on your AI knowledge, especially around RAG chatbots and agentic AI systems. Be ready to discuss your hands-on experience with LLM APIs and GenAI frameworks like LangChain or Hugging Face Transformers. The more specific examples you can provide, the better!
✨Showcase Real-World Impact
Prepare to talk about how your previous projects have made a measurable impact, particularly in life sciences. Highlight any evidence-driven projects you've worked on and how your AI solutions influenced patient access to treatments or improved decision-making in healthcare.
✨Collaboration is Key
Since the company values collaboration, be ready to discuss how you've worked with cross-functional teams in the past. Share examples of how you’ve collaborated with product, software, and platform teams to deliver scalable AI solutions, and emphasise your communication skills.
✨Emphasise Best Practices
Familiarise yourself with software engineering best practices like code reviews, testing, and CI/CD. Be prepared to explain how you ensure your AI solutions meet security, compliance, and responsible AI standards, as this will show you’re serious about quality and ethics in your work.
