At a Glance
- Tasks: Build and deploy AI applications that revolutionise investment processes.
- Company: Join a leading Buy Side Client in the heart of London.
- Benefits: Competitive daily rate, hybrid work model, and hands-on experience.
- Other info: Collaborate with investment professionals in a dynamic, innovative environment.
- Why this job: Make a real impact by solving complex business problems with AI.
- Qualifications: Experience with AI engineering, Python, and strong communication skills.
The predicted salary is between 60000 - 80000 € per year.
Leading Buy Side Client | London | Hybrid | Competitive Daily Rate
The Opportunity
Join a leading Buy Side Client building production AI systems that transform how investment professionals work. This isn't an R&D role—you'll ship LLM-powered applications that investment and finance teams depend on daily, while simultaneously building the governed AI platform that underpins the entire organisation.
- 50% embedding with business teams
- 50% platform engineering
What You'll Build
- Embedded AI Applications: Ship high-value LLM applications directly with Investment and Finance teams
- Turn ambiguous business problems into production-grade AI solutions
- Deploy agentic workflows using Claude and ChatGPT APIs
- Work alongside investment professionals to identify and solve real problems
- AI Platform Engineering: Build and extend governed AI platform: LLM gateway, model control layer, privacy proxy
- Develop MCP connectors for Salesforce, M365, deal flow systems, analytics platforms, and third-party data providers
- Implement logging, audit trails, observability, and evals tooling
- Design agentic workflows spanning multiple systems with proper tracing, scoring, and regression checks
- Ensure compliance with regulatory requirements (FCA, DORA)
Essential Skills:
- Production AI Engineering: Deep practical fluency with Claude and ChatGPT APIs, tool use, structured outputs, and prompting techniques
- Track record shipping LLM-powered applications that users depend on
- Experience with LLM gateways, privacy proxies, agent observability, or evals frameworks (even at hobby/prototype level)
- Software Engineering: Strong Python and TypeScript for production systems
- Modern Azure infrastructure and services
- Integration patterns: REST APIs, MCP, webhooks, SSO/Entra ID
- Production code experience in regulated or enterprise environments
- Business & Communication: Excellent communicator who can sit with investment professionals and turn conversations into code
- Ability to work with ambiguous business problems and ship concrete solutions
- Experience pairing with non-technical stakeholders
AI Forward Deployed Engineer in London employer: McCabe & Barton
Join a dynamic and innovative team at a leading Buy Side Client in London, where you will have the opportunity to work on cutting-edge AI applications that directly impact investment professionals. With a hybrid work model, competitive daily rates, and a culture that fosters collaboration and growth, this role offers a unique chance to develop your skills while contributing to meaningful projects. The company prioritises employee development and provides a supportive environment for tackling complex business challenges alongside industry experts.
StudySmarter Expert Advice🤫
We think this is how you could land AI Forward Deployed Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working with AI and finance. Use platforms like LinkedIn to connect and engage with them—ask questions, share insights, and show your enthusiasm for the role.
✨Tip Number 2
Prepare for those interviews! Research common questions for AI Forward Deployed Engineer roles and practice your responses. Be ready to discuss your experience with LLM applications and how you've tackled real-world problems in past projects.
✨Tip Number 3
Showcase your skills! Create a portfolio or GitHub repository that highlights your work with Claude and ChatGPT APIs. Include examples of your production-grade AI solutions and any integrations you've done—this will make you stand out!
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. Make sure to tailor your application to highlight your relevant experience and how you can contribute to building those high-value LLM applications.
We think you need these skills to ace AI Forward Deployed Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Forward Deployed Engineer role. Highlight your experience with LLM applications and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how you can contribute to our team. Be sure to mention specific skills like your fluency with Claude and ChatGPT APIs.
Showcase Your Problem-Solving Skills:In your application, give examples of how you've turned ambiguous business problems into concrete AI solutions. We love seeing real-world applications of your skills, so don't hold back!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it gets to the right people!
How to prepare for a job interview at McCabe & Barton
✨Know Your AI Stuff
Make sure you brush up on your knowledge of Claude and ChatGPT APIs. Be ready to discuss how you've used these tools in past projects, especially in shipping LLM-powered applications. The more specific examples you can provide, the better!
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled ambiguous business problems in the past. Think of concrete examples where you turned a vague challenge into a successful AI solution. This will demonstrate your ability to work closely with investment professionals.
✨Communicate Like a Pro
Since this role involves working with non-technical stakeholders, practice explaining complex technical concepts in simple terms. You want to show that you can bridge the gap between tech and business, so be ready for some role-play scenarios during the interview.
✨Get Familiar with Compliance
Understand the regulatory requirements like FCA and DORA that are relevant to the role. Be prepared to discuss how you would ensure compliance while developing AI solutions. This shows that you’re not just technically savvy but also aware of the bigger picture.
