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- Tasks: Shape AI usage across investment lifecycle and build internal AI-powered tools.
- Company: Leading growth equity firm investing in enterprise technology across the UK and Europe.
- Benefits: Competitive salary, performance bonus, hybrid work model, and leadership opportunities.
- Other info: Opportunity for career growth and to work directly with end users.
- Why this job: Be a key player in AI innovation with significant autonomy and impact.
- Qualifications: 3-5 years in software or applied AI engineering, strong Python skills.
The predicted salary is between 115000 - 175000 £ per year.
A leading growth equity firm investing in enterprise technology businesses across the UK and Europe is hiring an elite Forward Deployed AI Engineer - an influential, hands-on individual contributor who will play a foundational role in shaping how AI is used across the investment lifecycle.
We are interested in talking to a high achieving, high energy, fast tracker with around 3-5 years in a top tier environment, post-University. An AI native with an engineering background and mindset.
Importantly, you will have worked in high-context environments where engineers work directly with end users to deliver real-world AI systems - define the technical stack, set the roadmap, and own the end-to-end delivery of internal AI systems.
As the sole AI Engineer, you will have responsibility for E2E delivery (yes, including all development + implementation), and the chance to build from a blank slate, shaping the firm's AI capability, including sourcing, research, diligence, and workflows. This is a highly autonomous role with significant responsibility and the freedom to experiment, iterate, and drive impact quickly. You will move fluidly between rapid prototyping and production rigor, applying technical creativity to commercial decision-making.
More on the role:- Build internal AI-powered tools, systems and agents to streamline sourcing, research, diligence, and portfolio monitoring
- Design and deploy end-to-end LLM applications including research copilots, RAG systems, workflow automation, data enrichment, and deal intelligence tooling
- Ingest, clean, and analyse external datasets through scripts, pipelines, and lightweight ML components
- Integrate third-party APIs, datasets, scraping frameworks, and internal systems such as CRM and deal flow platforms
- Rapidly prototype MVPs, validate value with the investment team, and harden the most impactful tools into reliable internal products
- Build simple internal interfaces using FastAPI, Streamlit, or Next.js to enable intuitive adoption
- Implement evaluation, observability, and governance to ensure accuracy, reliability, security, and responsible use of AI systems
- Guide and coach the investment team on the latest tools, processes
- Circa 3-5 years in software engineering, applied AI engineering, ML engineering, or forward deployed roles
- Strong Python
- Experience building and deploying LLM applications (OpenAI, Anthropic, Gemini, etc.)
- Deep familiarity with RAG methodologies, embeddings, and vector databases (Pinecone, Weaviate, pgvector)
- Robust API integration experience, including working with third-party datasets, web APIs, or scrapers
- A product mindset, enjoys crafting scrappy prototypes that evolve into polished tools
- Strong communication skills and the ability to collaborate directly with non-technical business users
- Exposure to finance, enterprise data tooling, or B2B SaaS analytics is a bonus
The AI Engineer will thrive in real-world environments where delivery is all - settings where you work directly with end users, navigate ambiguous or evolving requirements, and need to understand the commercial context as deeply as the technical one.
It is envisaged that over time the role could evolve to include an element of trusted advisor / thought partner (i.e. for portfolio company / prospective investee company CEOs etc). Given the elite calibre and potential of the person we are after, there is a clear leadership path within the organisation.
Applied AI Engineer - fast-tracker, small VC equity leader in City of London employer: Richard Wheeler Associates
Contact Detail:
Richard Wheeler Associates Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI Engineer - fast-tracker, small VC equity leader in City of London
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or even casual coffee chats. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and engineering. This is your chance to demonstrate your hands-on experience and technical creativity, so make it shine!
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to AI engineering. Think about how you’d tackle real-world problems and be ready to discuss your thought process. We want to see that you can navigate ambiguity and deliver results.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage directly with us. Don’t miss out on the chance to join our team!
We think you need these skills to ace Applied AI Engineer - fast-tracker, small VC equity leader in City of London
Some tips for your application 🫡
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI shine through! We want to see how you've engaged with AI in real-world settings and how it excites you. Share specific projects or experiences that highlight your journey in this field.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for this role. Highlight your experience with LLM applications and any relevant tools you've used. We love seeing how your background aligns with our needs, so don’t hold back on the details!
Be Clear and Concise: Keep your application clear and to the point. We appreciate straightforward communication, especially when it comes to technical skills and experiences. Use bullet points where possible to make it easy for us to read through your achievements.
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 keen on joining our team at StudySmarter!
How to prepare for a job interview at Richard Wheeler Associates
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI applications, especially LLMs and RAG methodologies. Be ready to discuss specific projects you've worked on, how you approached challenges, and the impact of your solutions. This role is all about hands-on experience, so showcase your technical skills confidently!
✨Showcase Your Prototyping Skills
Prepare to talk about your experience with rapid prototyping and how you've turned scrappy ideas into polished tools. Bring examples of MVPs you've built and be ready to explain your thought process behind them. This will demonstrate your product mindset and ability to deliver real-world solutions.
✨Communicate Like a Pro
Since you'll be working closely with non-technical users, practice explaining complex concepts in simple terms. Think about how you can bridge the gap between technical and business needs. Good communication can set you apart, so be prepared to demonstrate this skill during the interview.
✨Understand the Business Context
Familiarise yourself with the investment lifecycle and how AI can enhance it. Research the company’s portfolio and think about how your skills can add value. Showing that you understand the commercial context as well as the technical one will make you a standout candidate for this role.