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Engineering Manager (AI Delivery Lead)

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Engineering Manager (AI Delivery Lead)
💰 £80,000 to £90,000
📍 London based, two office days per week, with some travel to the UAE.
Company & Role
This role sits with a global IT solutions provider standing up something genuinely different: an autonomous rapid prototyping pod for banking, insurance and fintech clients. A small, elite team that wins its own work, takes an ambiguous client problem, and turns it into a working AI prototype in four to five weeks, then hardens it into production. Your job is to make that machine run.
You will lead the pod, engineers across applied AI, agentic systems, full stack and quality, from discovery through to production, owning scope, timeline and delivery governance. This is an engineering management role, not a project management one. You need the technical background to read code, challenge engineers on risk and keep work flowing in parallel, in an environment where scope is rarely clear at the start and the answer is always a plan A, B and C rather than an excuse.
You are the team's leader and the delivery voice into the AI Director and pre-sales, translating engineering progress into commitments the business can stand behind.
Why This Role Stands Out
You are helping stand up a genuinely new capability, not maintaining someone else's. The pod is fully autonomous and converts prototypes straight into production delivery, so the pace is real and so is the ownership.
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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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
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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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
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.
There is proper leadership scope here: growing engineers, owning the pod's budget and hiring, shaping how a self-sufficient team works, with the compliance and governance dimension (including the EU AI Act) that regulated financial services delivery demands. This is engineering leadership with genuine technical teeth, at the sharp end of production AI.
There is a growing UAE dimension to the business too. Nothing is expected, but if working in or relocating to the UAE would ever appeal, they will back you to do it.
Key Responsibilities
- Lead a cross-functional pod (applied AI, agentic, full stack and QA) from discovery through to production delivery
- Work with the Forward Deployed Engineer and AI Director to shape client requirements into a delivery plan, phases and epics, defining who builds what and when
- Keep work flowing in parallel across the team, unblocking dependencies fast and holding a plan A, B and C when scope shifts
- Run sprint planning, backlog and delivery governance, keeping documentation and Jira genuinely current
- Ensure compliance with relevant regulation, including the EU AI Act, data residency and audit trail requirements
- Challenge engineers on technical decisions and risk, with the credibility to read code and question implementation choices
- Communicate engineering delivery clearly to the AI Director and pre-sales teams in business terms
- Own the pod as a cost centre, including hiring decisions and tooling and infrastructure investment
- Grow the team through regular feedback and pairing, and foster a blameless, continuous learning culture


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Ideal Experience
Essential
- An engineering management background, leading cross-functional software teams through delivery
- A genuine technical foundation, able to read code (Python, modern web stacks), review technical decisions and challenge engineers on risk
- Track record delivering projects with unclear or shifting scope, maintaining clarity and continuity across delivery phases
- Experience running parallel workstreams and keeping a whole team productive, not just administering tickets
- Strong, precise communication with both engineers and senior stakeholders
Desirable
- Financial services, banking, insurance or fintech experience, or other regulated environments
- AI and ML project delivery experience such as LLM solutions, agent orchestration or RAG
- Experience scaling delivery from discovery and MVP through to production
- Startup pace and ownership mindset rather than heavy process
- Understanding of the EU AI Act and regulated delivery governance
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