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O Partners

AI Deployment Engineer

London
£100k – £130k/yr
Posted about 12 hours ago
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AI Deployment Engineer - London - £130,000

We’re working with an innovative fintech business that is building out its internal AI capability and is looking for an AI Deployment Engineer to join the team.

This is a highly technical role focused on taking AI prototypes and turning them into reliable, production-ready solutions. You’ll own the infrastructure underneath AI deployments, including data pipelines, system integrations, APIs and the tooling required to ensure AI solutions operate reliably and at scale.

You’ll work closely with AI specialists to take concepts from prototype through to production, connecting AI solutions into the wider business ecosystem and building the technical foundations for future AI deployments.

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

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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.

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Strong

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.

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Key Responsibilities

  • Build and maintain production-grade data pipelines, storage and data infrastructure supporting AI deployments.
  • Integrate AI solutions with CRMs, ERPs, SaaS platforms and internal business systems.
  • Develop and maintain APIs, webhooks and middleware enabling AI agents to interact with business systems.
  • Take AI prototypes into production by hardening, scaling and improving reliability.
  • Build monitoring, logging and alerting across AI pipelines and infrastructure.
  • Manage data models, schemas and storage.
  • Troubleshoot integration issues, data inconsistencies and production problems.
  • Help establish the technical foundations for the organisation’s growing AI capability.

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What We’re Looking For

  • 3–5 years’ experience in software or data engineering, with strong exposure to integrations, data pipelines and production infrastructure.
  • Strong Python skills, with experience building production-grade pipelines from scratch.
  • Good understanding of REST APIs, webhooks, OAuth and event-driven architectures.
  • Experience with orchestration tools such as Airflow, Prefect or Dagster.
  • Experience working across AWS, Azure or GCP.
  • Strong experience with Docker and Kubernetes.
  • Experience integrating disparate business systems, SaaS platforms, databases and third-party APIs.
  • Comfortable working with Microsoft 365 and Microsoft Copilot.
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Skills

Python
Data Pipelines
REST APIs
Webhooks
OAuth
Event-Driven Architectures
Airflow
Prefect
Dagster
AWS
Azure
GCP
Docker
Kubernetes
System Integration
Microsoft Copilot

Location

London, England, United Kingdom

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