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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: Dynamic role with potential for leadership and collaboration with investment teams.
- 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 with 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'll 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
Skills and Experience:
- 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 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 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. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios. But don’t just stop there—be ready to discuss how you’ve tackled real-world problems in previous roles. We want to see your thought process and how you approach challenges!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. Don’t hesitate to follow up after applying; it shows your enthusiasm and commitment!
We think you need these skills to ace Applied AI Engineer - fast-tracker, small VC equity leader in London
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 you've engaged with AI technologies in your previous roles and how you envision using them in this position. Make it personal and relatable!
Tailor Your CV and Cover Letter: Don’t just send a generic CV! We’re looking for candidates who can demonstrate their experience in high-context environments and their ability to deliver real-world AI systems. Highlight relevant projects and skills that align with the job description.
Be Clear and Concise: We appreciate clarity! Keep your application straightforward and to the point. Use bullet points where necessary to make it easy for us to see your key achievements and skills at a glance.
Apply Through Our Website: Make sure to submit your application through our website. It’s the best way for us to track your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our team!
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 systems, especially LLM applications and RAG methodologies. Be ready to discuss your past projects in detail, showcasing how you've built and deployed AI solutions that have made a real impact.
✨Showcase Your Engineering Mindset
Prepare to talk about your engineering background and how it informs your approach to AI. Highlight experiences where you've worked directly with end users to deliver solutions, as this role demands a hands-on, user-focused mindset.
✨Demonstrate Your Prototyping Skills
Be ready to share examples of scrappy prototypes you've developed that evolved into polished tools. Discuss your process for rapid prototyping and how you validate ideas with stakeholders, as this is crucial for the role.
✨Communicate Effectively
Since you'll be collaborating with non-technical business users, practice explaining complex technical concepts in simple terms. Show that you can bridge the gap between technical and commercial contexts, which is key for success in this position.