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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 36000 - 60000 £ 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 while 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 and 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 London employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field and let them know you're on the lookout for opportunities. Attend meetups, webinars, or tech conferences to meet potential employers and showcase your skills.
✨Tip Number 2
Show off your projects! Create a portfolio that highlights your experience with AI/ML solutions. Include case studies of your work, especially those involving cloud platforms and modern frameworks. This will give you an edge when chatting with hiring managers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and understanding of AI principles. Practice coding challenges and be ready to discuss your approach to deploying AI solutions. We all know that confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s a great way to get noticed by Kainos and other companies looking for top talent. Plus, we’re here to support you every step of the way in landing that dream job!
We think you need these skills to ace Lead AI Engineer in London
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've got!
Tailor Your Application: Take a moment to customise your application for the Lead AI Engineer role. We love seeing how you can connect your past experiences to the specific requirements listed in the job description. It shows us you’re genuinely interested!
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that are easy to read. Use bullet points if needed to make your achievements stand out!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
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
As a Lead AI Engineer, you'll need to collaborate effectively with others. Think of examples from your past experiences where you've mentored junior developers or worked in a team to solve complex problems. Highlight your interpersonal skills and how you foster a culture of innovation.
✨Understand Responsible AI
Kainos values responsible AI practices, so be prepared to discuss ethical considerations and model interpretability. Familiarise yourself with the principles of responsible AI and be ready to share your thoughts on how to implement these in real-world applications.
