Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- 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 Bristol employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer in Bristol
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech world, especially those in AI. Attend meetups, webinars, or conferences where you can chat with industry folks and get your name out there.
✨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 do and set you apart from the crowd.
✨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 communicate effectively with both techies and non-techies.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities at Kainos that are just waiting for someone 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 Lead AI Engineer in Bristol
Some tips for your application 🫡
Showcase Your Experience: When writing your application, make sure to highlight your experience with deploying AI/ML solutions. Use specific examples that demonstrate your skills in prompt engineering and model evaluation. We want to see how you've tackled real-world challenges!
Be Clear and Concise: Keep your application clear and to the point. Avoid jargon unless it's necessary, and make sure your passion for AI shines through. We appreciate straightforward communication, so let us know why you're excited about this role!
Tailor Your Application: Don’t just send a generic application! Tailor it to the Lead AI Engineer role by aligning your skills with the job description. Mention your experience with cloud platforms like Azure or AWS, and how you’ve implemented responsible AI practices.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
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 worked in a team to solve complex problems or mentored junior developers. Highlight your interpersonal skills and how you foster a culture of innovation.
✨Understand Responsible AI
Be prepared to discuss responsible AI principles and ethical considerations. This is crucial for the role, so think about how you've implemented these practices in your previous work and be ready to share your thoughts on model interpretability and compliance standards.
