Find a job 
Featured Companies 
Featured Universities 
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: Earn up to £65,000 plus benefits, with remote-first flexibility.
- Why this job: Make a real impact by delivering AI that drives business success.
- Qualifications: Strong experience in AI production delivery and understanding of AI fundamentals.
- Other info: Enjoy a supportive culture with opportunities for meaningful collaboration.
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 Reading 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 Reading
✨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 the attention it deserves. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Lead AI Engineer (Enterprise | Greenfield AI) in Reading
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’re comfortable with the tech stack we use and can hit the ground running.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of applications better 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 Stuff
Make sure you brush up on your AI fundamentals before the interview. Be ready to discuss your hands-on experience with deploying AI solutions, especially in production environments. They’ll want to hear about specific projects you've worked on and how you tackled challenges.
✨Showcase Your Impact
Prepare to talk about how your work has made a difference in previous roles. Focus on metrics and outcomes rather than just the technical details. They’re looking for someone who can own results, so be ready to explain how your contributions led to real business impact.
✨Communicate Clearly
Since you'll need to explain AI behaviour and limitations to non-technical stakeholders, practice simplifying complex concepts. Use relatable examples to demonstrate your understanding and ensure that everyone is on the same page during discussions.
✨Embrace the Greenfield Challenge
This role is all about building from scratch, so show your enthusiasm for greenfield projects. Be prepared to discuss how you would approach designing and iterating AI systems in a new environment, and share any relevant experiences where you’ve shaped best practices.
