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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 working model, competitive salary, and opportunity to shape the future of AI.
- Why this job: Take ownership of groundbreaking AI technology and make a real impact in finance.
- Qualifications: Experience in LLM/RAG systems and strong Python skills required.
- Other info: Collaborate with industry experts and enjoy excellent career growth opportunities.
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 in City of London employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding AI Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the AI and FinTech space on LinkedIn or at meetups. We can’t stress enough how personal connections can open doors that applications alone can’t.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and RAG systems. We love seeing practical examples of your work, so make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and understanding AI architectures. 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. Plus, we’re always looking for passionate individuals who want to shape the future of AI with us.
We think you need these skills to ace Founding AI Engineer in City of London
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI and its potential shine through. We want to see that you’re not just looking for a job, but that you’re genuinely excited about building predictive intelligence platforms and making an impact in the FinTech space.
Highlight Relevant Experience: Make sure to showcase your experience with LLM/RAG systems and any end-to-end delivery projects you've led. We’re keen on seeing how your background aligns with the responsibilities of the Lead AI Engineer role, so don’t hold back on those details!
Tailor Your Application: Customise your CV and cover letter to reflect the specific skills and experiences mentioned in the job description. We appreciate when candidates take the time to connect their expertise with what we’re looking for, so make it personal!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it’s super easy – just follow the prompts!
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 translating financial services use cases into AI features, it’s crucial to have a grasp of the financial industry. Familiarise yourself with current trends and challenges in finance to show that you can connect market foresight with actionable intelligence.
✨Be Ready to Collaborate
This position requires working closely with the CTO and guiding junior engineers. Prepare to discuss your experience in mentoring and collaborating with others. Highlight any past experiences where teamwork led to successful project outcomes.
