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- Tasks: Lead the development of cutting-edge AI solutions and mentor a talented team.
- Company: Join Kainos, a forward-thinking tech company focused on innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make a real impact in AI while collaborating with industry experts.
- Qualifications: Experience in AI/ML deployment, strong Python skills, and cloud platform expertise.
- Other info: Fast-paced environment with a culture of continuous learning and innovation.
The predicted salary is between 43200 - 72000 £ per year.
hackajob is collaborating with Kainos to connect them with exceptional tech professionals for this role. As a Lead AI Engineer at Kainos, you will deliver advanced AI solutions leveraging state-of-the-art machine learning, generative and agentic AI technologies. You will drive the adoption of modern AI frameworks, AIOps best practices and scalable cloud-native architectures. Your role will involve hands-on technical delivery, collaborating with customers to translate business challenges into trustworthy AI solutions and ensuring responsible AI practices throughout. As a technical mentor, you will foster a culture of innovation, continuous learning, and engineering excellence. It is a fast-paced environment, so it is important for you to make sound, reasoned decisions. You will do this whilst learning about new technologies and approaches, with talented colleagues that will help you to develop and grow. You will support your colleagues and more junior developers, providing direction support as you solve challenging problems together.
Minimum (essential) Requirements
- Demonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation (RAG), model evaluation, and monitoring using metrics (e.g. precision, recall, NDCG and drift detection).
- Strong Python skills with a grounding in software engineering best practices (CI/CD, testing, code reviews etc).
- Experience developing solutions at scale on cloud platforms (Azure & AWS), containerisation and orchestration tools such as Kubernetes and Docker.
- Expertise in data engineering for AI: handling large-scale, unstructured, and multimodal data.
- Understanding of responsible AI principles, model interpretability, and ethical considerations.
- Strong interpersonal skills and team working.
Desirable
- Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost).
- Experience with data storage for AI, vector databases, semantic search, and knowledge graphs.
- Contributions to open-source AI projects or research publications.
- Familiarity with AI security, privacy, and compliance standards e.g. ISO42001.
Lead AI Engineer in Cambridge employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer in Cambridge
✨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 landing that Lead AI Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving modern frameworks and cloud solutions. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex AI concepts in simple terms, as you'll need to collaborate with customers and mentor junior developers.
✨Tip Number 4
Don't forget to apply through our website! We’re always looking for talented individuals like you to join our team at Kainos. Your next big opportunity could be just a click away!
We think you need these skills to ace Lead AI Engineer in Cambridge
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with deploying AI/ML solutions. We want to see your hands-on skills in action, so don’t hold back on showcasing your Python prowess and any cloud platform experience you have!
Tailor Your Application: Take a moment to customise your application for the Lead AI Engineer role. We love seeing how your background aligns with our needs, especially when it comes to responsible AI practices and modern frameworks.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to understand and directly related to the job description. No fluff, just the good stuff!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at Kainos!
How to prepare for a job interview at hackajob
✨Know Your AI Stuff
Make sure you brush up on your knowledge of modern AI/ML solutions, especially around prompt engineering and model evaluation. Be ready to discuss specific projects where you've deployed these technologies, as well as the metrics you used to measure success.
✨Show Off Your Python Skills
Since strong Python skills are essential for this role, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice writing clean, efficient code and be familiar with software engineering best practices like CI/CD and testing.
✨Talk About Teamwork
This role involves collaboration and mentoring, so be prepared to share examples of how you've worked effectively in teams. Highlight any experiences where you've supported junior developers or fostered a culture of innovation and continuous learning.
✨Understand Responsible AI
Kainos values responsible AI practices, so make sure you can discuss ethical considerations and model interpretability. Familiarise yourself with the principles of responsible AI and be ready to explain how you've applied them in your previous work.
