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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: 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: Hands-on experience in AI production and a solid 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) employer: Climate17
Contact Detail:
Climate17 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI Engineer (Enterprise | Greenfield AI)
✨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
Showcase your skills! Create a portfolio of 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 AI fundamentals and be ready to discuss real-world applications. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with non-technical stakeholders.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. 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)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Lead AI Engineer. Highlight your hands-on experience with AI solutions and any relevant projects that showcase your ability to deliver real impact.
Showcase Your Skills: Don’t just list your skills; demonstrate them! Include specific examples of how you've designed, built, and deployed AI systems in production environments. We want to see your journey!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your experience and how it aligns with our needs. We appreciate brevity but also want to understand your thought process.
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 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 know how you’ve tackled real-world challenges, so have some examples up your sleeve!
✨Showcase Your Impact
This role is all about delivering results, so be prepared to talk about how your previous projects have made a difference. Focus on success metrics and how your work has driven adoption and business impact. Numbers speak volumes, so if you can quantify your achievements, do it!
✨Communicate Clearly
You’ll need to explain complex AI concepts to non-technical stakeholders, so practice simplifying your language. Think about how you can convey the behaviour and limitations of AI systems in a way that’s easy to understand. This will show you can bridge the gap between tech and business.
✨Embrace the Greenfield Mindset
Since this is a greenfield role, they’ll be looking for someone who’s comfortable shaping best practices from scratch. Be ready to discuss how you approach building and iterating on AI systems in an uncharted environment. Highlight your adaptability and creativity in problem-solving!
