Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and develop cutting-edge AI systems while collaborating with diverse teams.
- Company: Join a forward-thinking tech company focused on innovation and collaboration.
- Benefits: Enjoy competitive pay, health perks, remote work options, and growth opportunities.
- Other info: Dynamic role with continuous learning and career advancement potential.
- Why this job: Be at the forefront of AI technology and make a real difference in product development.
- Qualifications: Experience in software programming, cloud platforms, and strong teamwork skills required.
The predicted salary is between 50000 - 70000 £ per year.
The AI Engineer II is a mid-level position responsible for engineering AI based products and maintenance. As a mid-level engineer in this role, you will work closely with senior engineers and non-technical business stakeholders, contributing to the entire lifecycle of building and maintaining emerging LLM-based products. An important aspect of this role would be product design and execution bearing cost efficiency and speed.
The ideal candidate would have skills in software programming, building agentic systems, mathematics, and DevOps (including container operations, CI/CD, and cloud engineering). Good communication skills with an ability to demystify LLMs and agentic systems are a must, as stakeholders in AI products include software engineering teams as well as non‑technical business partners.
Responsibilities:- Design, develop, and optimise agentic AI systems.
- Work with Product/business stakeholders to capture and establish requirements for AI products.
- Steer consolidation of dataset requirements, acquiring data, management, and version control for AI applications.
- Monitor AI products in production, setting metrics to identify performance (accuracy, retrieval rates, hit rates), and establish corrective measures for restoring performance.
- Identify and implement appropriate tools for monitoring AI product performance in production.
- Ownership of technical documentation related to design, model selection, experiments, and production infrastructure.
- Continual learning and self‑improvement with a focus on latest trends, techniques, and best practices in AI.
- Ability to work in a team.
- Experience with cloud computing platforms like AWS.
- Familiarity with containerization and orchestration tools like Docker and Kubernetes.
- Experience with version control systems like Git.
- Ability to leverage coding agents for accelerated software development.
- Nice to have: Masters in a specific field such as Statistics, Data Science, Machine Learning, or AI.
- Knowledge of SQL and NoSQL databases including construction of queries, query optimisation, and schema design.
- API development using standard tools such as FastAPI or Flask.
- Good understanding of Machine Learning algorithms and models (Language processing models such as GPT, BERT, etc).
AI Engineer II employer: Zonda
Contact Detail:
Zonda Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer II
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field, attend meetups, and engage in online forums. The more people you know, the better your chances of landing that AI Engineer II role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and agentic systems. 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 communication skills. Practice explaining complex AI concepts in simple terms, as you'll need to connect with both technical and non-technical stakeholders.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes the application process smoother for everyone involved.
We think you need these skills to ace AI Engineer II
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the AI Engineer II role. Highlight your experience with cloud platforms, containerization, and any relevant projects you've worked on. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for this position. Don’t forget to mention your communication skills and how you can bridge the gap between technical and non-technical stakeholders.
Showcase Your Projects: If you've worked on any AI-related projects, make sure to include them in your application. Whether it's a personal project or something from your previous job, we love seeing practical examples of your work and how you’ve tackled challenges in AI engineering.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our company culture there!
How to prepare for a job interview at Zonda
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI systems, especially LLMs like GPT and BERT. Be ready to discuss how you've designed or optimised agentic systems in the past. This will show that you’re not just familiar with the theory but have practical experience too.
✨Communicate Clearly
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Think about how you can demystify AI for someone who might not have a tech background. This skill is crucial for the role!
✨Showcase Your DevOps Skills
Be prepared to talk about your experience with cloud platforms like AWS and tools like Docker and Kubernetes. Highlight any projects where you’ve implemented CI/CD pipelines or managed container operations. This will demonstrate your hands-on experience in maintaining AI products.
✨Bring Examples of Your Work
Have a few examples ready that showcase your coding skills, particularly with version control systems like Git. If you’ve developed APIs using FastAPI or Flask, or worked with SQL/NoSQL databases, make sure to mention these experiences. Real-world examples can really set you apart!