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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: Strong hands-on experience in AI production and a solid grasp of AI fundamentals.
- 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 Nottingham 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 Nottingham
✨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
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from candidates who are genuinely excited about building impactful AI solutions.
We think you need these skills to ace Lead AI Engineer (Enterprise | Greenfield AI) in Nottingham
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Lead AI Engineer role. Highlight your hands-on experience in delivering AI solutions and any relevant projects you've worked on that showcase your ability to own outcomes.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI and how you can contribute to our greenfield projects. Share specific examples of how you've successfully built and deployed AI systems in the past.
Showcase Your Technical Skills: Don’t forget to mention your experience with enterprise data platforms, Python, SQL, and any LLM-based systems. We want to see that you have a solid understanding of AI fundamentals and can explain AI behaviour to non-technical stakeholders.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Climate17
✨Know Your AI Fundamentals
Make sure you have a solid grasp of AI fundamentals, especially around safety, monitoring, and evaluation. Be ready to discuss how these concepts apply to real-world scenarios, as this will show your understanding of the responsibilities that come with deploying AI.
✨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 clear about the impact these systems had on the business. This will demonstrate your capability to own outcomes.
✨Communicate Effectively with Stakeholders
Practice explaining complex AI behaviours and limitations in simple terms. Since you'll be working closely with non-technical stakeholders, being able to bridge that gap is crucial. Think of examples where you've successfully communicated technical details to a non-technical audience.
✨Embrace the Greenfield Environment
Familiarise yourself with the concept of greenfield projects and be prepared to discuss how you would approach building AI systems from scratch. Share your thoughts on shaping best practices and patterns in a new environment, as this aligns perfectly with what the role entails.
