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Principal Artificial Intelligence (AI) Platform Engineer/Architect

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Principal Artificial Intelligence (AI) Platform Engineer/Architect
We are looking for an AI Platform Engineer to drive our vision of AI-augmented engineering across our enterprise of 500+ engineers. In this role, you will empower our highly skilled workforce to deliver high-quality value to our clients faster and with a better Developer Experience (DevEx) than ever before. We need someone who combines deep technical expertise with practical platform engineering to create the scalable infrastructure, processes, and tooling that enable our teams to integrate AI into their development workflows safely and seamlessly.
Acting as both architect and hands-on builder, you will articulate our vision for AI-accelerated development practices, design platforms that embed AI at every phase of the SDLC, and champion adoption across our organization. We are seeking a highly skilled engineer who has recently specialized into AI technologies and can confidently guide our teams on both architecture and implementation.
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.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
The Role
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Define and evolve the vision for AI-enabled SDLC practices, translating business and technical strategy into concrete platform capabilities and processes
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Design and implement scalable AI platform infrastructure (SDKs, frameworks, deployment pipelines) that enables rapid, safe integration of AI into all phases of development—from coding and testing to deployment and monitoring
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Build operational processes, templates, and playbooks that guide teams through AI implementation while maintaining consistency, quality, and auditability
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Partner with teams across the organization to operationalize AI tools for SDLC acceleration (e.g., copilot-style code generation, test automation, documentation, performance analysis)
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Create and maintain self-service tooling for model evaluation, prompt engineering, A/B testing, monitoring, and compliance validation


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Establish and evolve patterns for data pipeline management, RAG/retrieval design, model versioning, endpoint management, and agentic orchestration
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Develop comprehensive documentation, architectural guidance, runbooks, and examples that reduce onboarding time and accelerate team adoption
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Evangelize AI-enabled practices through presentations, office hours, and direct team engagement—building credibility and driving adoption across the organization
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Provide escalation pathways for architecture questions and unblock teams on complex integration challenges
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Implement monitoring, observability, and governance systems that provide transparency without creating bottlenecks
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Collaborate with security, compliance, and data teams to embed safety guardrails into platform capabilities
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Participate in incident response and continuously harden the platform based on production learnings
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