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- Tasks: Lead the design and production of AI systems for a cutting-edge predictive intelligence platform.
- Company: High-growth FinTech startup in Central London with a dynamic founding team.
- Benefits: Competitive salary, meaningful equity, and hybrid working model.
- Why this job: Join at ground level to shape AI in finance and make a real impact.
- Qualifications: Strong experience in LLM engineering and Python; STEM degree required.
- Other info: Fast-paced environment with excellent career growth opportunities.
The predicted salary is between 100000 - 120000 £ per year.
A high-growth FinTech startup in London is building an AI-powered Predictive Intelligence Platform for corporates and financial institutions. Their technology connects market events, client data, and emerging opportunities through advanced agentic AI and RAG-based systems, helping financial institutions anticipate client needs before they arise.
They have built a live MVP in record time, with enterprise client demos underway, and are now hiring a Lead AI Engineer to join as permanent hire number four in the founding technology team. This is a rare opportunity to join at the inflection point — a hands-on, high-ownership, high-impact role where you’ll shape the AI core of a company redefining predictive intelligence in finance.
Role Overview
Reporting directly to the CTO, you’ll lead the design and productionisation of the company’s core AI systems. You will architect, implement, evaluate, and scale RAG pipelines, agentic workflows, and LLM-based intelligence frameworks, driving real-world impact across financial markets. The role is approximately 80% hands-on and 20% strategic, covering Python engineering, system architecture, and model evaluation, while collaborating closely with product and domain experts.
Key Responsibilities
- Build and deploy RAG pipelines, agentic AI workflows, and LLM integration frameworks
- Own AI evaluation, guardrails, and observability systems
- Translate financial workflows into scalable AI capabilities
- Collaborate directly with the CTO and external development teams
- Help shape the AI roadmap and mentor future hires
About You
- Strong experience in LLM engineering, RAG systems, prompt orchestration, and agentic architectures
- Proven experience delivering ML/AI systems into production environments
- Excellent Python engineering and system design skills
- Familiarity with APIs, MLOps, and cloud deployment (AWS, GCP, or Azure)
- Clear communicator, comfortable in fast-paced, early-stage environments
- STEM degree required; MSc in AI, Computer Science, or a related field preferred
- You have experience in financial services/regulated industry
- You have B2B experience
What’s on Offer
- £100k-£120k base salary plus meaningful equity
- Join at ground level (hire number four) with real ownership and influence
- Work with an exceptional founding team from top-tier consulting, technology, and finance backgrounds
- Hybrid working model: 2–3 days a week in Central London
- Visa sponsorship not available
Founding Lead AI Engineer in Slough employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding Lead AI Engineer in Slough
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. The more you engage, the better your chances of landing that Lead AI Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to LLM engineering and RAG systems. This will give you an edge when discussing your hands-on experience during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on Python engineering and system design. Practice coding challenges and be ready to discuss your approach to building scalable AI capabilities.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Founding Lead AI Engineer in Slough
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI and its potential in finance shine through. We want to see how your experience aligns with our mission to redefine predictive intelligence!
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for this role. Highlight your relevant skills in LLM engineering and RAG systems, and don’t forget to mention any experience you have in financial services!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so make sure your key achievements and experiences are easy to spot. Remember, we’re looking for someone who can communicate effectively!
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 to join our founding team!
How to prepare for a job interview at Harnham
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLM engineering, RAG systems, and agentic architectures. Be ready to discuss specific projects you've worked on and how they relate to the role. This is a hands-on position, so demonstrating your technical expertise will be key!
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled challenges in previous roles, especially in fast-paced environments. Think of examples where you've built or deployed AI systems that had a real-world impact, particularly in financial services. This will show that you can think on your feet and deliver results.
✨Understand the Company’s Vision
Do your homework on the startup's mission and the predictive intelligence platform they're developing. Being able to articulate how your skills align with their goals will impress the interviewers and show that you're genuinely interested in being part of their journey.
✨Be Ready to Collaborate
Since this role involves working closely with the CTO and other teams, be prepared to discuss your experience in collaborative settings. Share examples of how you've successfully worked with cross-functional teams to deliver projects, as this will highlight your ability to fit into their culture.
