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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
Locations
Lead AI Engineer (Enterprise | Greenfield AI) in Hampshire, Portsmouth 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 Hampshire, Portsmouth
✨Tip Number 1
Network like a pro! Reach out to folks in the AI space, attend meetups, and join online forums. The more connections we make, the better our chances of landing that dream job.
✨Tip Number 2
Showcase your skills! Create a portfolio of your AI projects, even if they’re personal or academic. We want to demonstrate our hands-on experience and ability to deliver real results.
✨Tip Number 3
Prepare for interviews by practising common AI-related questions and scenarios. We should be ready to explain our thought process and how we tackle challenges in AI deployment.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can tailor our approach based on the specific role and company culture.
We think you need these skills to ace Lead AI Engineer (Enterprise | Greenfield AI) in Hampshire, Portsmouth
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 rather than just listing tasks. Use metrics or specific examples to illustrate how your contributions improved AI systems or business outcomes.
Be Clear and Concise: Keep your application straightforward and to the point. Avoid jargon unless it's necessary, and ensure that anyone reading your application can easily understand your experience and qualifications.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. This way, we can ensure your application gets the attention it deserves and you can stay updated on your application status.
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 ready to discuss the outcomes and metrics you tracked to measure success.
✨Communicate Clearly with Non-Technical Stakeholders
Since you'll need to explain AI behaviour and limitations to non-technical stakeholders, practice simplifying complex concepts. Use relatable analogies or examples to demonstrate your ability to bridge the gap between technical and non-technical audiences.
✨Emphasise Your Impact-Driven Mindset
This role is all about delivering real value, so be prepared to discuss how you've focused on outcomes rather than just building prototypes. Share instances where your work has directly impacted business goals or improved user experiences.
