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For Companies At a Glance
- Tasks: Lead the design, build, and deployment of impactful AI systems in a greenfield environment.
- Company: Join a forward-thinking tech company focused on real-world AI solutions.
- Benefits: Competitive salary up to £65,000, remote-first work, and collaborative culture.
- Why this job: Make a real impact by delivering AI systems that matter and drive business success.
- Qualifications: Hands-on experience in AI production, strong understanding of AI fundamentals, and stakeholder communication skills.
- Other info: Enjoy a supportive environment with clear success measures and opportunities for growth.
The predicted salary is between 46800 - 78000 £ per year.
Location: UK (Remote-first)
Travel: Regular on-site collaboration initially (weekly for the first couple of months), then approx. one in-person session every two weeks
Salary: Up to £65,000 + benefits
We’re hiring a hands-on Lead AI Engineer to take technical ownership of greenfield AI use cases in an enterprise environment. This is a pure individual contributor role with no line management, no programme ownership. You’ll be responsible for designing, building, deploying, and iterating AI systems that are actually used by the business. The emphasis is on real delivery: shipping AI into production, monitoring performance and safety, and improving outcomes over time based on adoption and impact.
What You’ll Do
- Own AI use cases end-to-end: design → build → deploy → monitor → iterate
- Build AI systems that work with enterprise data, including LLM-based and agentic workflows
- Define and track success metrics for AI use cases, focusing on adoption and business impact
- Implement monitoring, evaluation, and safety controls for live AI systems
- Work closely with business stakeholders to ensure AI solutions are trusted, usable, and valuable
- Operate in a largely greenfield environment, shaping patterns and best practices as you go
The Tech Environment
- The team is platform-flexible. Experience with one or more of the following is relevant:
- Enterprise data & AI platforms (e.g. Databricks, Microsoft Fabric, Azure AI services, or comparable)
- LLM-based systems (RAG, agentic workflows, prompt engineering, evaluation)
- Python and SQL in production environments
- AI monitoring, evaluation, and lifecycle management
- Low-code or assisted AI tooling is absolutely fine — what matters is a solid understanding of how AI systems actually work, including their risks and limitations.
What We’re Looking For
- Strong hands-on experience delivering AI solutions into production
- A solid grasp of AI fundamentals, safety, monitoring, and evaluation
- Comfortable owning outcomes rather than just building prototypes
- Able to explain AI behaviour and limitations to non-technical stakeholders
- Happy in a senior individual contributor role, focused on impact rather than hierarchy
What This Role Is Not
- Not a people management role
- Not an AI strategy or architecture-only position
- Not a research-only or POC-only role
This role is for someone who enjoys building, shipping, and improving AI systems that matter.
Why Join
- Genuine greenfield AI work with real ownership
- Clear success measures based on impact, not slide decks
- Supportive, delivery-focused environment
- Remote-first with meaningful in-person collaboration
If you’re an AI engineer who enjoys turning ideas into working systems, understands the responsibility that comes with deploying AI, and wants to focus on delivery rather than titles we’d love to hear from you.
How to apply: If this role looks like it is for you, please send your CV to Kris Kobi: kris@climate17.com
Lead AI Engineer (Enterprise | Greenfield AI) in Glasgow employer: Climate17
Contact Detail:
Climate17 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer (Enterprise | Greenfield AI) in Glasgow
✨Tip Number 1
Network like a pro! Reach out to folks in the AI space, attend meetups, and join online forums. The more connections you make, the better your chances of landing that Lead AI Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those that demonstrate your ability to ship systems into production. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and being ready to discuss real-world applications of AI. Be ready to explain how you've tackled challenges in previous projects.
✨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 hearing from passionate candidates who are eager to make an impact.
We think you need these skills to ace Lead AI Engineer (Enterprise | Greenfield AI) in Glasgow
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your hands-on experience with AI solutions. We want to see how you've designed, built, and deployed systems in the past, so don’t hold back on those details!
Showcase Your Impact: When describing your previous roles, focus on the outcomes of your work. We’re all about real delivery here at StudySmarter, so let us know how your contributions made a difference in your projects.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and make it easy for us to understand your skills and experiences.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the attention you deserve!
How to prepare for a job interview at Climate17
✨Know Your AI Fundamentals
Make sure you brush up on your AI fundamentals before the interview. Be ready to discuss how AI systems work, their risks, and limitations. This will show that you have a solid grasp of the subject and can communicate effectively with both technical and non-technical stakeholders.
✨Showcase Your Hands-On Experience
Prepare to share specific examples of AI solutions you've delivered into production. Highlight your role in the design, build, and deployment processes, and be ready to discuss the outcomes and impact of your work. This will demonstrate your ability to own AI use cases end-to-end.
✨Understand the Business Impact
Familiarise yourself with how AI can drive business value. Be prepared to discuss success metrics you've defined and tracked in previous projects. This shows that you’re not just about building prototypes but are focused on delivering real results that matter to the business.
✨Embrace the Greenfield Environment
Since this role involves working in a greenfield environment, be ready to talk about how you would shape patterns and best practices. Share your thoughts on how to implement monitoring and safety controls for live AI systems, as this will highlight your proactive approach to building trustworthy AI solutions.
