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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: Enjoy a competitive salary, remote work flexibility, and opportunities for professional growth.
- Why this job: Make a tangible impact by delivering AI systems that truly matter to businesses.
- Qualifications: Strong hands-on experience in AI production and a solid understanding of AI fundamentals.
- Other info: Collaborative, supportive culture with a focus on delivery and innovation.
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 Preston 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 Preston
✨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 complex concepts in simple terms for non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to make an impact in the AI field.
We think you need these skills to ace Lead AI Engineer (Enterprise | Greenfield AI) in Preston
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 demonstrate your ability to own outcomes.
Showcase Your Impact: When detailing your previous roles, focus on the impact of your work. Use metrics and examples to illustrate how your AI systems improved business outcomes or user experiences. We want to see how you’ve made a difference!
Be Clear and Concise: Keep your application straightforward and to the point. Avoid jargon unless it’s necessary, and make sure to explain any technical terms clearly. Remember, we want to understand your thought process and how you communicate with non-technical stakeholders.
Apply Through Our Website: We encourage you to apply through our website for a smoother 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 where you’ve taken ownership and delivered real results.
✨Speak Their Language
Since this role involves working closely with business stakeholders, practice explaining complex AI concepts in simple terms. Think about how you can convey the behaviour and limitations of AI systems without getting too technical. This will show that you can bridge the gap between tech and business.
✨Showcase Your Impact
Prepare examples that highlight your ability to track success metrics and improve outcomes over time. They’re looking for someone who focuses on delivery and impact, so be ready to discuss how your work has made a difference in previous roles.
✨Get Familiar with the Tech Stack
Familiarise yourself with the tools and platforms mentioned in the job description, like Databricks or Azure AI services. Even if you haven’t used them all, showing that you understand their relevance and how they fit into the AI landscape will impress your interviewers.
