At a Glance
- Tasks: Lead generative AI projects, mentor peers, and design impactful AI solutions.
- Company: Join a cutting-edge AI Centre of Excellence with a collaborative spirit.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on continuous learning and development.
- Why this job: Shape the future of AI while working on innovative and meaningful projects.
- Qualifications: Experience with LLMs and strong backend engineering skills required.
The predicted salary is between 70000 - 90000 £ per year.
About the role
Lead generative AI initiatives, mentor peers, set engineering standards, and design and deploy AI solutions to enhance products and processes.
Responsibilities
- Partner with product managers, data scientists, and engineers to research, validate, and deliver high-impact Generative AI use cases.
- Design and build APIs and microservices that integrate AI capabilities into internal and external workflows.
- Develop, fine-tune, and deploy LLM-based applications (e.g., chatbots, assistants, knowledge extraction tools).
- Architect scalable AI infrastructure on cloud platforms (AWS, GCP, or Azure), leveraging containerisation and IaC.
- Implement CI/CD pipelines and enforce best practices for secure, compliant AI deployment.
- Build intuitive interfaces that enable teams to interact effectively with AI-driven features.
- Continuously optimise performance, reliability, and scalability of AI systems.
Qualifications
- Hands-on experience with LLMs (such as GPT, BERT, Llama, Gemini) and applying them to real-world problems.
- Strong backend engineering expertise, including RESTful APIs and micro-services design.
- Proficiency in Python/JavaScript and familiarity with AI frameworks (e.g., LangChain, Pydantic).
- Solid understanding of cloud computing (AWS, GCP, or Azure), containerisation (Docker, Kubernetes) and Infrastructure-as-Code (Terraform).
- Proven problem-solving skills and ability to thrive in fast-paced environments.
- Excellent communication and collaboration skills across diverse teams.
Preferred Qualifications
- Proficiency in C# or Java.
- Front-end development experience with JavaScript/TypeScript and frameworks such as React.
- Experience developing Generative AI applications, including model fine-tuning and prototyping.
- Awareness of ethical AI practices and emerging standards in AI governance.
- Track record of rapid prototyping with measurable ROI.
- Familiarity with distributed systems and large-scale data processing.
- Contributions to open-source projects or a strong GitHub portfolio.
- High technical curiosity and eagerness to learn new platforms.
- Experience in the payments industry (strong plus).
Senior AI Engineer in London employer: 0026 Checkout Technology Ltd
As a Senior AI Engineer at our AI Centre of Excellence, you will join a dynamic and innovative team dedicated to pushing the boundaries of generative AI. We offer a collaborative work culture that fosters creativity and continuous learning, alongside competitive benefits and opportunities for professional growth in a cutting-edge environment. Located in a vibrant tech hub, our company provides unique advantages such as access to industry-leading resources and a network of like-minded professionals, making it an exceptional place to advance your career in AI.
Contact Details:
0026 Checkout Technology Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field, attend meetups, and join online forums. The more people you know, the better your chances of hearing about job openings before they even hit the market.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs or generative AI. This is your chance to demonstrate your expertise and make a lasting impression on potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to AI engineering and be ready to discuss your past experiences and how they relate to the role.
✨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 the attention it deserves.
We think you need these skills to ace Senior AI Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Senior AI Engineer. Highlight your hands-on experience with LLMs and backend engineering expertise. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for generative AI and how you’ve tackled real-world problems. Let us know why you’re excited about joining our AI Centre of Excellence.
Showcase Your Projects:If you've worked on any cool AI projects, don’t hold back! Include links to your GitHub portfolio or any open-source contributions. We love seeing practical applications of your skills!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at 0026 Checkout Technology Ltd
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs like GPT and BERT. Be ready to discuss how you've applied these technologies in real-world scenarios, especially in generative AI projects. This will show that you’re not just familiar with the theory but have hands-on experience.
✨Showcase Your Engineering Skills
Prepare to talk about your backend engineering expertise, particularly in designing RESTful APIs and microservices. Have examples ready that demonstrate your proficiency in Python or JavaScript, and be prepared to discuss any relevant frameworks you've used, like LangChain or Pydantic.
✨Cloud Knowledge is Key
Since the role involves architecting scalable AI infrastructure, make sure you can discuss your experience with cloud platforms like AWS, GCP, or Azure. Highlight any projects where you’ve implemented containerisation or Infrastructure-as-Code, as this will show you understand modern deployment practices.
✨Communication is Crucial
This role requires collaboration with product managers and data scientists, so be ready to demonstrate your communication skills. Share examples of how you've worked effectively in diverse teams and how you’ve built intuitive interfaces for AI-driven features. This will highlight your ability to bridge technical and non-technical discussions.
