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- Tasks: Lead AI projects and develop innovative LLM solutions that drive real business impact.
- Company: Join a dynamic, private-equity-backed consumer services company transforming through AI.
- Benefits: Enjoy a competitive salary, bonus, pension, and hybrid working model.
- Why this job: Shape the future of AI in a hands-on role with significant growth opportunities.
- Qualifications: Experience in AI engineering and a passion for impactful technology.
- Other info: Work in a collaborative environment with a focus on mentorship and career development.
The predicted salary is between 48000 - 72000 £ per year.
Do you want to shape how LLMs are deployed at scale in a real business? Have you built RAG or agentic systems that moved beyond experimentation? Are you motivated by measurable customer and commercial impact, not demos? A private-equity-backed consumer services business is scaling its Data Science & AI capability as part of a multi-year transformation. Following an award-winning data programme, the company now has an established AI function and is investing further in LLM-powered assistants, RAG pipelines, voice/chat intelligence and early agentic workflows across both customer-facing and internal products.
This role is a hands-on individual contributor position, sitting between Data Science and AI Engineering. You will lead AI proof-of-concepts, design retrieval and context strategies, contribute to the AI architecture, and ensure solutions are robust, scalable and commercially grounded. The role spans the full AI lifecycle, from data preparation and model evaluation through to deployment and optimisation.
Key responsibilities- Lead development of LLM and AI proof-of-concepts
- Design and implement RAG pipelines and agentic workflows
- Define evaluation frameworks for LLM quality and response accuracy
- Partner with product and engineering on chat flows and continuous improvement
- Contribute to AI platform architecture and best practices
- Mentor junior ML / AI engineers (no formal line management)
- Salary: £80,000 base + 10% bonus
- Pension: 5% matched
- Working model: Hybrid, 3 days per week (Tuesday & Wednesday fixed)
- Location: Central London
- Stack: Python, Databricks, RAG, vector databases, Azure (preferred), LangChain / LangFuse
- Visa: This role cannot sponsor
Interested? Please apply below.
Artificial Intelligence Engineer in England employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in England
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving LLMs or RAG systems. We want to see your hands-on experience, so make sure to highlight any proof-of-concepts you've led or contributed to.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We recommend practising common AI engineering questions and scenarios, so you can demonstrate your expertise and thought process during the interview.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Artificial Intelligence Engineer in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Senior AI Engineer. Highlight your experience with LLMs, RAG systems, and any hands-on projects that showcase your skills in AI and Data Science. We want to see how you’ve made a measurable impact in previous roles!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our mission at StudySmarter. Don’t forget to mention specific projects or achievements that demonstrate your expertise in AI engineering.
Showcase Your Technical Skills: In your application, be sure to highlight your technical skills relevant to the stack we use, like Python, Databricks, and Azure. If you've worked on AI proof-of-concepts or designed retrieval strategies, let us know! We love seeing practical examples of your work.
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 get all the updates directly from us. Plus, it’s super easy – just follow the prompts and submit your materials!
How to prepare for a job interview at Harnham
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, Databricks, and Azure. Brush up on your knowledge of RAG pipelines and vector databases, as these will likely come up during technical discussions.
✨Showcase Your Impact
Prepare to discuss specific projects where you've made a measurable impact. Companies want to see how your work has driven customer or commercial success, so have examples ready that highlight your contributions to AI proof-of-concepts or agentic systems.
✨Understand the AI Lifecycle
Familiarise yourself with the full AI lifecycle, from data preparation to deployment and optimisation. Be ready to talk about your experience in each stage and how you ensure solutions are robust and scalable.
✨Be Ready to Mentor
Since mentoring junior engineers is part of the role, think about your approach to guiding others. Prepare examples of how you've supported colleagues in the past, whether through formal mentorship or collaborative projects.
