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- Tasks: Shape AI capabilities and build internal tools for investment processes.
- Company: Leading growth equity firm focused on enterprise technology.
- Benefits: Competitive salary, performance bonus, and hybrid work model.
- Why this job: Be a pioneer in AI within finance and make a real impact.
- Qualifications: 5+ years in software or applied AI engineering with strong Python skills.
- Other info: Autonomous role with opportunities for rapid prototyping and career growth.
The predicted salary is between 160000 - 175000 £ per year.
A leading growth equity firm investing in enterprise technology businesses across the UK and Europe is hiring a Senior Applied AI Engineer - an elite, hands-on individual contributor who will play a foundational role in shaping how AI is used across the investment lifecycle.
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. There are no plans for the AI Engineer to build a team.
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. This is a highly autonomous architect-led 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:
- 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 Senior 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, albeit in a small way, to include an element of trusted advisor / thought partner (i.e. for portfolio company / prospective investee company CEOs etc).
AI Engineer, E2E Product Delivery, Finance employer: Richard Wheeler Associates
Contact Detail:
Richard Wheeler Associates Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer, E2E Product Delivery, Finance
✨Tip Number 1
Network like a pro! Reach out to folks in the finance and AI sectors on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those that demonstrate end-to-end delivery. Share your work on GitHub or personal websites, and make sure to highlight any tools or systems you've built that align with the role.
✨Tip Number 3
Prepare for the interview by diving deep into the company’s current AI initiatives. Understand their investment strategies and think about how your skills can enhance their processes. Tailor your responses to show you’re not just a fit for the role, but a perfect match for their vision.
✨Tip Number 4
Don’t forget to 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. Let’s get you that dream job!
We think you need these skills to ace AI Engineer, E2E Product Delivery, Finance
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python and LLM applications in your application. We want to see how you've used these skills in real-world scenarios, especially in high-context environments.
Tailor Your Application: Don’t just send a generic CV and cover letter. Tailor them to reflect the specific requirements of the Senior AI Engineer role. We love seeing candidates who take the time to connect their experiences with what we’re looking for.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so make sure your key achievements and experiences stand out without unnecessary fluff.
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 the role. Plus, it shows you’re keen on 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 applications, especially in finance. Be ready to discuss your experience with LLM applications and RAG methodologies. They’ll want to see that you can talk the talk and walk the walk!
✨Showcase Your Prototyping Skills
Prepare to share examples of your past projects where you rapidly prototyped MVPs. Highlight how you validated these with users and iterated based on feedback. This role is all about building impactful tools, so demonstrate your hands-on experience.
✨Communicate Like a Pro
Since you'll be working closely with non-technical business users, practice explaining complex technical concepts in simple terms. Think about how you can convey your ideas clearly and effectively, as strong communication skills are key for this position.
✨Understand the Business Context
Familiarise yourself with the investment lifecycle and how AI can enhance it. Show that you understand the commercial implications of your work and can navigate ambiguous requirements. This will set you apart as someone who can bridge the gap between tech and business.