DELTACLASS TECHNOLOGY SOLUTIONS LIMITED
Artificial Intelligence Engineer

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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.
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.
See breakdownIt 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.
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.
- 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.
“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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