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- Tasks: Lead the development of cutting-edge AI solutions and mentor a team of tech enthusiasts.
- Company: Join Kainos, a forward-thinking company at the forefront of AI innovation.
- Benefits: Enjoy competitive pay, flexible working, and opportunities for continuous learning.
- Why this job: Make a real impact in AI while collaborating with talented professionals in a dynamic environment.
- Qualifications: Experience in deploying AI/ML solutions and strong Python skills are essential.
- Other info: Fast-paced culture with excellent growth opportunities and a focus on responsible AI practices.
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 employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech world, especially those in AI. Attend meetups or webinars related to AI and machine learning. You never know who might have a lead on that perfect role at Kainos!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving modern frameworks like PyTorch or TensorFlow. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and understanding of CI/CD practices. Practice coding challenges and be ready to discuss your experience with deploying AI solutions in production.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for passionate individuals who are eager to drive innovation in AI at Kainos.
We think you need these skills to ace Lead AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead AI Engineer role. Highlight your experience with AI/ML solutions, Python skills, and any cloud platform expertise. We want to see how your background aligns with what Kainos is looking for!
Showcase Your Projects: Include specific projects where you've deployed AI solutions or worked with modern frameworks. This is your chance to shine! We love seeing real-world applications of your skills, so don’t hold back.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about AI and how you can contribute to Kainos. Be genuine and let your personality come through. We appreciate a good story that connects your experiences to the role!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensure it gets into the right hands. Plus, it shows you’re serious about joining the team 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 this will show your hands-on experience.
✨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 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.
