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- Tasks: Design and deploy cutting-edge AI systems for a predictive intelligence platform.
- Company: High-growth AI/FinTech startup with a focus on innovation.
- Benefits: Hybrid work model, competitive salary, and opportunity to shape AI strategy.
- Why this job: Take ownership of groundbreaking AI projects and make a real impact.
- Qualifications: Experience in LLM/RAG systems and strong Python skills.
- Other info: Collaborate with industry experts and enjoy excellent career growth.
The predicted salary is between 36000 - 60000 £ 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
- 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 AI and FinTech space on LinkedIn or at meetups. A personal connection can often get your foot in the door faster than a CV.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and agentic systems. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and AI concepts. Practice coding challenges and be ready to discuss your past projects in detail.
✨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!
We think you need these skills to ace Founding AI Engineer
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI shine through! We want to see how excited you are about building predictive platforms and working with cutting-edge technology. Share any personal projects or experiences that highlight your passion.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Founding AI Engineer role. Highlight your experience with LLMs, RAG systems, and any relevant projects you've led. We love seeing how your skills align with our needs!
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured documents that make it easy for us to see your qualifications. Avoid jargon unless it's relevant, and focus on what makes you a great fit for the role.
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 shows you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Harnham
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python, LLMs, and RAG systems. Brush up on your knowledge of agentic workflows and how they integrate into enterprise platforms. Being able to discuss these technologies confidently will show that you’re the right fit for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've led end-to-end delivery of AI systems. Think about challenges you faced and how you overcame them. This will demonstrate your ability to take ownership and navigate complex technical landscapes.
✨Understand the Financial Context
Since this role involves working with financial institutions, it’s crucial to understand their needs and challenges. Familiarise yourself with how predictive AI can transform financial services, and be ready to translate use cases into practical AI features during the interview.
✨Engage with the CTO's Vision
Research the company’s mission and the CTO’s background. Be prepared to discuss how you can contribute to shaping the architecture and long-term AI strategy. Showing alignment with their vision will set you apart as a candidate who’s genuinely interested in the role.
