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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 applied AI, strong Python skills, and product mindset.
- Other info: Autonomous role with opportunities for rapid prototyping and career growth.
The predicted salary is between 130000 - 160000 £ 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 developer 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.
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 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).
Senior Applied AI Engineer, Finance employer: Richard Wheeler Associates
Contact Detail:
Richard Wheeler Associates Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Applied AI Engineer, Finance
✨Tip Number 1
Network like a pro! Reach out to folks in the finance and AI sectors 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
Show off your skills! Create a portfolio showcasing your AI projects, especially those related to finance. We recommend using platforms like GitHub to share your code and demonstrate your hands-on experience with LLM applications and API integrations.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. We suggest doing mock interviews with friends or using online platforms to get comfortable discussing your experience in applied AI engineering and how it relates to real-world applications.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it shows you’re genuinely interested in being part of our team!
We think you need these skills to ace Senior Applied AI Engineer, Finance
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Applied AI Engineer role. Highlight your experience with LLM applications and any relevant projects that showcase your skills in Python and AI engineering. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're excited about this role and how you can contribute to shaping our AI capabilities. Be sure to mention your experience in high-context environments and your product mindset.
Showcase Your Projects: If you've built any AI tools or systems, don’t hold back! Include links or descriptions of your projects that demonstrate your ability to deliver end-to-end solutions. We love seeing real-world applications of your skills!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Richard Wheeler Associates
✨Know Your AI Stuff
Make sure you brush up on your applied AI engineering knowledge, especially around LLM applications and RAG methodologies. Be ready to discuss your past projects in detail, showcasing how you've built and deployed AI systems that have made a real impact.
✨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 developed and be ready to explain the thought process behind them, especially how they addressed user needs.
✨Communicate Like a Pro
Since you'll be working closely with non-technical business users, practice explaining complex technical concepts in simple terms. Think of scenarios where you've successfully collaborated with end users and how you navigated any challenges.
✨Understand the Business Context
Familiarise yourself with the finance sector and how AI can drive value in investment processes. Be prepared to discuss how your technical skills can align with commercial goals, demonstrating that you understand both the tech and the business side of things.