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DELTACLASS TECHNOLOGY SOLUTIONS LIMITED

Artificial Intelligence Engineer

Leeds
Posted about 17 hours ago
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AI Solution Development

  • Design, develop and deploy AI-powered applications and services.
  • Build scalable agentic AI solutions using modern orchestration frameworks.
  • Develop RAG pipelines using vector embeddings, semantic search and knowledge retrieval patterns.
  • Implement conversational AI assistants and intelligent workflow automation.
  • Integrate AI models with enterprise systems, APIs and data platforms.
  • Develop prompt engineering, evaluation and guardrail frameworks.

Machine Learning and LLM Engineering

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.

P

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.

  • Train, fine-tune and optimise machine learning and generative AI models where appropriate.
  • Build model evaluation and monitoring capabilities.
  • Develop model serving and inference pipelines.
  • Implement responsible AI controls and validation processes.
  • Evaluate emerging AI technologies and recommend adoption opportunities.

Platform and Cloud Engineering

  • Build and deploy solutions on Google Cloud Platform.
  • Develop containerised applications using Docker and Kubernetes.
  • Work with GKE, Vertex AI, BigQuery, Cloud Run and related GCP services.
  • Implement CI/CD pipelines and automated testing frameworks.
  • Ensure scalability, resilience, security and observability of production services.

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Data and Integration

  • Integrate AI solutions with structured and unstructured data sources.
  • Build ingestion pipelines from SharePoint, APIs, databases and cloud storage.
  • Develop vector stores and embedding pipelines.
  • Work closely with Data Engineers to optimise data access patterns.
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Skills

AI Solution Development
Agentic AI
RAG Pipelines
Conversational AI
Prompt Engineering
Machine Learning
LLM Engineering
Model Fine-tuning
Google Cloud Platform
Docker
Kubernetes
Vertex AI
BigQuery
CI/CD
Vector Databases
API Integration

Location

Leeds, England, United Kingdom

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