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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 AI innovation.
- Benefits: Attractive salary, health perks, remote flexibility, and growth opportunities.
- Other info: Dynamic team environment with continuous learning and career advancement.
- Why this job: Be at the forefront of AI technology and make a real difference.
- Qualifications: Bachelor's degree and 3+ years in AI product development required.
The predicted salary is between 50000 - 60000 £ 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.
Qualifications & Skills
- Must have Bachelor’s degree in computer science, Engineering, or a related field.
- 3+ years of experience in AI product development or Machine Learning.
- Proficient in Python.
- Built and deployed at least two LLM‑based or NLP‑heavy products in a real setting likely using agentic frameworks like LangGraph, LangChain, AutoGen etc.
- Strong mathematical, analytical, and problem‑solving skills.
- Experience with retrieval systems, embeddings, and vector DBs like Weaviate or Pinecone.
- Ability to structure and execute an Agentic AI project from start to completion.
- Excellent communication and teamwork skills; 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 in Glasgow employer: Zonda
Contact Detail:
Zonda Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer II in Glasgow
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those LLM-based products you've built. This gives you a chance to demonstrate your expertise and makes you stand out 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 engage with both technical and non-technical stakeholders. We want you to shine!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace AI Engineer II in Glasgow
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with AI product development and any specific projects you've worked on. We want to see how you've used your programming skills, especially in Python, to build LLM-based products.
Keep It Clear and Concise: When writing your application, aim for clarity. Use straightforward language to explain your experience and how it relates to the role. Remember, we’re looking for good communication skills, so make it easy for us to understand your background.
Tailor Your Application: Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific requirements of the AI Engineer II role. Mention your familiarity with tools like Docker, Kubernetes, and cloud platforms like AWS to catch our eye.
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 keen on joining the StudySmarter team!
How to prepare for a job interview at Zonda
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI products, especially LLMs and agentic systems. Be ready to discuss your experience with Python and any frameworks you've used, like LangGraph or LangChain. The more you can demonstrate your technical expertise, the better!
✨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 will show your ability to bridge the gap between teams.
✨Showcase Your Projects
Prepare to talk about at least two LLM-based or NLP-heavy products you've built and deployed. Highlight your role in the project lifecycle, from design to execution, and be ready to discuss the challenges you faced and how you overcame them.
✨Ask Smart Questions
At the end of the interview, don’t forget to ask insightful questions about the company’s AI strategy or the tools they use. This shows your genuine interest in the role and helps you gauge if it's the right fit for you. Plus, it gives you a chance to engage with your interviewers!