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PRACYVA

Enterprise Architect - AI

London
Posted about 21 hours ago
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Role Requirements

  • Technical Expertise:
    • Across all areas of AI, including:
      • Machine learning and predictive modelling
      • MLOps and ML pipeline industrialisation
      • LLMOps, prompt engineering, embeddings, and vector search
      • Large Language Models (LLMs), hosting, tuning, and optimisation
      • Gen AI and model orchestration
      • Agentic AI architectures, tool-use patterns, memory, and multi-agent workflows

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.

Start with a chat, not a search bar

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.

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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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It searches the market for you

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.

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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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Strong

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.

  • Knowledge:

    • Vector databases
    • Distributed systems
    • Scalable AI workload architecture

  • Understanding:

    • Enterprise data platforms
    • Data sourcing patterns and constraints

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  • Experience:

    • Designing scalable cloud-native AI architectures (e.g., Azure, GCP)

  • Ability:

    • Translating complex architectures into reusable enterprise design patterns
Trusted by 25,000+ job seekers

“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”

Jessica, London

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Skills

Machine Learning
MLOps
LLMOps
Prompt Engineering
Vector Search
Large Language Models
Generative AI
Agentic AI Architectures
Vector Databases
Distributed Systems
Cloud-native Architecture
Azure
GCP
Enterprise Design Patterns
Data Sourcing Patterns

Location

London, England, United Kingdom

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