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- Tasks: Build and deploy AI tools to revolutionise investment processes and drive impactful results.
- Company: Leading growth equity firm focused on enterprise technology across Europe.
- Benefits: Competitive salary, performance bonuses, hybrid work model, and leadership opportunities.
- Other info: Autonomous role with significant responsibility and potential for career advancement.
- Why this job: Shape the future of AI in finance and make a real difference in investment strategies.
- 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 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
✨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 before they even meet you.
✨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 your 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 take the initiative to reach out directly. Don’t hesitate—get your application in and let’s chat about how you can make an impact!
We think you need these skills to ace Applied AI Engineer - fast-tracker, small VC equity leader
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the role of an Applied AI Engineer. Highlight your hands-on experience in building AI systems and any relevant projects you've worked on that showcase your engineering mindset.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've successfully delivered AI solutions in high-context environments and how you can contribute to shaping our AI capabilities.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical prowess! Mention your experience with Python, LLM applications, and API integrations. We want to see how you’ve applied these skills in real-world scenarios, so be specific!
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 shows your enthusiasm for 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 hands-on experience with Python and any projects where you've built or deployed AI tools. This role is all about practical application, so showcase your technical creativity!
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled ambiguous requirements in past roles. Think about times when you had to work directly with end users to deliver solutions. Highlight your ability to prototype quickly and iterate based on feedback, as this will resonate well with the fast-paced environment.
✨Communicate Like a Pro
Since you'll be collaborating with non-technical business users, practice explaining complex concepts in simple terms. During the interview, demonstrate your strong communication skills by engaging with the interviewer and asking insightful questions about their needs and challenges.
✨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 will set you apart as a candidate who can bridge the gap between technology and business.