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- Tasks: Build and iterate on Generative AI solutions to transform team operations.
- Company: Join Checkout.com’s innovative AI Centre of Excellence in London.
- Benefits: Competitive salary, health benefits, remote work, and growth opportunities.
- Why this job: Make a real impact with cutting-edge AI technology and collaborative teams.
- Qualifications: Degree in Computer Science or related field; experience with LLMs and backend engineering.
- Other info: Dynamic environment with excellent career growth and learning opportunities.
The predicted salary is between 60000 - 80000 ÂŁ per year.
As a Software Engineer within Checkout.com’s AI Centre of Excellence, you will rapidly build and iterate on Generative AI solutions to transform how cross-functional teams operate. You will work with teams from across Checkout.com’s portfolio of products and services who all have a real customer‑first philosophy. You will design, build, and deploy AI solutions that enhance products and streamline business processes in collaboration with cross‑functional teams. You will also be an avid user of coding agents and know how to get the most out of them.
Responsibilities
- Partner with product managers, non‑technical business users and engineers to research, validate, and deliver high‑impact Generative AI use cases.
- Design and build user‑facing products that leverage AI capabilities for optimising internal workflows with a focus on adoption and user satisfaction.
- Build, deploy, measure and iterate on LLM‑based applications (e.g., agents, knowledge extraction, automation solutions).
- Develop end‑to‑end AI solutions on cloud platforms (AWS, GCP, or Azure) taking a build‑it‑yourself attitude to the entire development lifecycle including test suites, deployment pipelines (CICD), agent evaluations and observability.
- Design systems that continuously optimise performance, reliability, and scalability of AI systems.
Qualifications
- Educational Background: Bachelor's or Master's degree in Computer Science, Engineering, or related field.
- AI & LLM Expertise: Hands‑on experience with LLMs (e.g., GPT, Gemini, Claude Code) and applying them to real‑world problems.
- Backend Proficiency: Strong backend engineering expertise, including RESTful APIs and micro‑services design.
- Technical Stack: Proficiency in Python/JavaScript/Typescript and familiarity with AI frameworks (e.g., LangChain, PydanticAI and Google Agent Development Kit).
- Cloud & Infrastructure: Solid understanding of cloud computing (AWS, GCP, or Azure), containerisation (Docker, Kubernetes), and Infrastructure‑as‑Code (Terraform).
- Soft Skills: Proven problem‑solving skills and ability to thrive in fast‑paced environments, with excellent communication and collaboration skills across diverse teams.
Preferred Qualifications
- Proficiency in Python.
- Frontend 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.
- Contributions to open‑source projects or a strong GitHub portfolio.
- High technical curiosity and eagerness to learn new platforms.
Software Engineer, AI Centre of Excellence Software engineering London employer: Checkout Ltd
Contact Detail:
Checkout Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer, AI Centre of Excellence Software engineering London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI and coding agents. This is your chance to demonstrate what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by practising common technical questions and coding challenges. Use platforms like LeetCode or HackerRank to sharpen your skills and get comfortable with problem-solving on the spot.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Checkout.com.
We think you need these skills to ace Software Engineer, AI Centre of Excellence Software engineering London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with LLMs and backend engineering in your application. We want to see how you've tackled real-world problems using AI, so don’t hold back on those examples!
Tailor Your Application: Take a moment to customise your application for the role. Mention specific projects or experiences that align with our focus on Generative AI solutions and cross-functional collaboration. It shows us you’re genuinely interested!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon unless it’s relevant. We appreciate a well-structured application that gets straight to the point!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Checkout Ltd
✨Know Your AI Stuff
Make sure you brush up on your knowledge of Generative AI and LLMs like GPT and Claude Code. Be ready to discuss how you've applied these technologies in real-world scenarios, as this will show your hands-on experience and understanding of the field.
✨Showcase Your Coding Skills
Prepare to demonstrate your backend engineering expertise, especially with RESTful APIs and micro-services design. Bring examples of your work in Python or JavaScript/TypeScript, and be ready to talk about any projects where you've built or deployed AI solutions.
✨Collaboration is Key
Since you'll be working with cross-functional teams, highlight your communication and collaboration skills. Think of specific instances where you've partnered with product managers or non-technical users to deliver impactful solutions, and be prepared to share those stories.
✨Get Familiar with Cloud Platforms
Understand the cloud platforms mentioned in the job description, like AWS, GCP, or Azure. Be ready to discuss your experience with containerisation tools like Docker and Kubernetes, and how you've used Infrastructure-as-Code practices in your previous projects.