MBN Solutions
Forward Deployed Engineer

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Forward Deployed Engineer - Applied AI
Up to £80,000 base + equity | London, with UK client travel
Your first Forward Deployed Engineer role. AI that makes it into production.
You’ve built software that people rely on. You’re comfortable in Python, have practical experience with AI and ML, and want to get closer to the problems your technology solves. Now you want more involvement: understanding the customer’s challenge, deciding what to build, shipping it and seeing the difference it makes.
This is an opportunity to move into Forward Deployed Engineering at an early-stage AI company building agentic systems for wealth management. You’ll work closely with an experienced leadership team invested in developing you, with access to senior clients and real ownership of production systems.
You don’t need to have held an FDE title before. You do need solid engineering foundations, curiosity and the confidence to take responsibility as you learn.
Why this opportunity stands out
- Leadership you can learn from. Work directly with a leadership team that will help you develop your technical judgement, customer confidence and ability to take projects from an initial conversation through to production.
- Clients who will stretch you. Work with established wealth management firms, engaging with technology leaders, compliance teams and senior advisers. Learn how to turn complex, sometimes ambiguous requirements into systems people can trust.
- Substantial engineering challenges. Build AI agents for real workflows where accuracy, security and reliability matter. Your work will involve Python, models, evaluations, cloud infrastructure and the practical challenges of running AI in production.
- A say in the product. What you learn on client projects will feed directly into the core platform. You’ll help build reusable capabilities that make each deployment better than the last.
- Room to grow. Join while the business and its FDE function are still taking shape, with the opportunity to build your skills and take on broader responsibility as the company grows.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What you’ll do
You’ll work across customer, product and ML teams, helping take AI projects from an initial problem through to a working system. That will include:
- Working directly with clients to understand their workflows and define what a successful solution looks like.
- Building and deploying agentic AI systems for tasks such as document generation, client information capture, file reviews and compliance monitoring.
- Writing production Python across backend services, agents, data pipelines and evaluation tooling.
- Building test sets and evaluation metrics, measuring performance against real customer requirements and improving the results.
- Deploying into customers’ Azure environments, with attention to security, access and reliability.
- Turning lessons from client work into reusable components for the wider platform.
- Supporting the systems you ship, including participating in on-call support when customers need it.
What you’ll bring
You might currently be a software engineer, backend engineer, ML engineer or applied AI engineer. Your job title matters less than what you’ve built and how you approach problems. We’re looking for:


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- Strong Python skills and experience building and maintaining production software.
- Practical AI or ML engineering experience, including evaluating and deploying systems beyond a prototype.
- Confidence working with cloud infrastructure. Azure is particularly useful; AWS or GCP experience is relevant too.
- Clear communication. You can explain technical decisions, ask useful questions and work through uncertainty with others.
- An interest in customer-facing engineering. You want to understand the business problem as well as the technology.
- Thoughtful views on AI agents, including retrieval, tool use, evaluation and guardrails.
Experience with customers, financial services or another regulated sector would be useful, but isn’t essential. You don’t need to arrive knowing every tool in the stack.
The technology
Python, FastAPI, Pydantic, Azure, PostgreSQL, OpenAI and Anthropic models, agent evaluation frameworks, Microsoft 365 integrations and financial services CRM systems.
What’s on offer
- Base salary up to £80,000, plus equity.
- Close access to an experienced leadership team committed to your development.
- The opportunity to build your FDE career through hands-on work with established clients.
- Ownership of meaningful engineering decisions and a direct contribution to the product.
- An early-stage environment with high trust and room to take initiative.
- London office presence, with travel to client sites across the UK.
Interested?
Apply with your CV and a short note about something you’ve built, the part you owned and why you’d like to move into Forward Deployed Engineering.
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