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- Tasks: Design and implement AI-powered automation solutions that deliver real business value.
- Company: Join a leading heavy asset client at the forefront of applied AI.
- Benefits: Earn up to £105k, enjoy an 8% pension, and comprehensive benefits.
- Why this job: Make a tangible impact in AI while working with cutting-edge technologies.
- Qualifications: Strong experience with LLMs, Python or JavaScript, and excellent communication skills.
- Other info: Dynamic, fast-paced environment with opportunities for growth and innovation.
The predicted salary is between 80000 - 105000 £ per year.
Do you want to build a predictive AI platform that surfaces opportunities before clients even know they exist?
Have you led end-to-end delivery of LLM/RAG/agentic systems in production?
Ready to become the technical owner of an intelligence engine at an early-stage startup?
A high-growth AI/FinTech startup is building a predictive intelligence platform for financial institutions. Their system connects external market events, client risks and revenue opportunities through real-time agentic AI. Backed by senior ex-consulting and enterprise technology leaders, they've already built a functioning MVP and are now hiring their first in-house Lead AI Engineer to take ownership of the core intelligence layer.
You'll work directly with the CTO, shaping the architecture, roadmap and long-term AI strategy. This role suits a builder who wants ownership, deep technical scope and the chance to define the product from the ground up.
The Lead AI Engineer will architect and productionise advanced LLM/RAG systems, design agentic workflows, own evaluations and guardrails, and integrate AI modules into a scalable enterprise-grade platform. You'll collaborate with domain experts from corporate and investment banking, helping turn market foresight into actionable intelligence.
Key responsibilities
• Design and deploy RAG pipelines, agentic workflows and LLM-based intelligence modules
• Build Python-based AI components, APIs and microservices
• Own evaluation frameworks, observability, guardrails and model governance
• Integrate AI systems into production environments and enterprise workflows
• Work closely with the CTO and guide junior/external engineers
• Translate financial-services use cases into practical AI features
Key details
• Working model: Hybrid (3 days/week, Central London)
• Tech: Python, LLMs, RAG, agentic systems, vector stores, cloud
• Visa: Cannot sponsor
Interested? Please apply below.
Founding AI Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding AI Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving LLMs and automation tools. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by practising common technical questions related to AI solutions and prompt engineering. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨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 Founding AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Founding AI Engineer role. Highlight your experience with LLMs and prompt engineering, and don’t forget to showcase any relevant projects that demonstrate your skills in building AI-driven workflows.
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. Be sure to mention specific examples of your work that relate to the responsibilities listed in the job description.
Showcase Your Technical Skills: We want to see your technical prowess! Include any hands-on experience you have with tools like LangChain or automation platforms. If you've built prototypes or integrated systems, make sure to highlight those achievements clearly.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Harnham
✨Know Your AI Stuff
Make sure you brush up on your knowledge of Large Language Models and prompt engineering. Be ready to discuss specific projects where you've integrated LLMs with enterprise systems, as this will show your hands-on experience.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've identified business problems and delivered AI solutions. Think about times when you designed workflows or implemented RAG pipelines, and be ready to explain the impact of your work.
✨Communicate Clearly
Since excellent communication is key, practice explaining complex technical concepts in simple terms. You might need to translate business needs into technical solutions, so being clear and concise will help you stand out.
✨Familiarise Yourself with Tools
Get comfortable with automation platforms like UiPath or Power Automate, and be prepared to discuss how you've used them in past projects. Showing that you can hit the ground running with these tools will impress your interviewers.
