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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: Fast-paced environment with clear leadership path and real-world impact.
- 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'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 environs 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 Islington 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 Islington
✨Tip Number 1
Network like a pro! Reach out to people in your field on LinkedIn or at industry events. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews! Research the company and its culture, and be ready to discuss how your skills align with their needs. We want you to shine, so practice common interview questions and have your own questions ready to show your interest.
✨Tip Number 3
Showcase your projects! If you’ve built any AI tools or systems, make sure to highlight them during your conversations. We love seeing real-world applications of your skills, so don’t be shy about sharing your successes.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always looking for high achievers like you, so 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 Islington
Some tips for your application 🫡
Read the Job Description Carefully: Before you start writing, make sure to thoroughly read the job description. We want to see that you understand what we're looking for, so tailor your application to highlight how your skills and experiences align with the role.
Showcase Your Technical Skills: As an AI Engineer, your technical prowess is key! Be sure to include specific examples of your experience with Python, LLM applications, and any relevant projects you've worked on. We love seeing real-world applications of your skills!
Be Authentic and Personal: Let your personality shine through in your application. We’re looking for high-energy, fast-trackers who are passionate about AI. Share your journey, what excites you about this role, and why you want to join us at StudySmarter.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive all the information we need and ensures your application gets the attention it deserves. We can’t wait to hear from you!
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 tools that have made a real impact.
✨Showcase Your Engineering Mindset
Prepare to talk about your engineering background and how it complements your AI skills. Highlight experiences where you've worked directly with end users to deliver solutions, as this role requires a hands-on approach and an understanding of commercial contexts.
✨Demonstrate Your Prototyping Skills
Be ready to share examples of scrappy prototypes you've created that evolved into polished tools. Discuss your process for rapid prototyping and how you validated these tools with stakeholders, as this will show your product mindset.
✨Communicate Clearly
Since you'll be collaborating with non-technical business users, practice explaining complex technical concepts in simple terms. Good communication is key, so think of ways to demonstrate your ability to bridge the gap between tech and business during the interview.