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Annapurna

Data & AI Engineer

City of London
Posted about 23 hours ago
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Data & AI Engineer

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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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.

Our client is seeking a pragmatic, hands-on Data & AI Engineer to design, build, and operate AI-powered applications and agents that solve real business problems. You'll join our client's team to enhance existing AI solutions, create new AI capabilities that improve workflows and decision-making, and work closely with business stakeholders and engineers to embed domain expertise into robust, production-grade AI systems.

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Key Skills & Experience

  • Python software development - Strong, production-level coding skills to build reliable, maintainable AI services.
  • End-to-end software delivery - Experience designing, building, testing, deploying, and operating production-grade systems.
  • AI/LLM application development - Hands-on experience creating AI or LLM-based applications used by real users, not just experimenting with consumer tools.
  • AI system lifecycle - Exposure to prototyping, data preparation, evaluation, deployment, monitoring, and continuous improvement of AI systems.
  • AI evaluation and metrics - Ability to design and run evaluations, and measure model/agent quality, reliability, safety, and business impact.
  • Working with multiple model providers - Understanding of different model families, trade-offs in latency, cost, context limits, and deployment constraints.
  • Prompt and agent design - Experience treating prompts and agent instructions as versioned, testable software artifacts.
  • Systems integration - Integrating AI with APIs, enterprise applications, data platforms, and both structured and unstructured data.
  • Advanced AI techniques - Familiarity with retrieval-augmented generation, tool calling, structured outputs, agent orchestration, and workflow automation.
  • Model adaptation foundations - Understanding when to use prompting, retrieval, fine-tuning, and how to prepare and evaluate data and models for post-training.
  • Business and data understanding - Ability to grasp complex workflows, rules, and processes, and translate them into AI-enabled solutions.
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Skills

Python
AI/LLM Application Development
Software Delivery
AI System Lifecycle
AI Evaluation
Prompt Engineering
Agent Design
Systems Integration
Retrieval-Augmented Generation
Tool Calling
Structured Outputs
Agent Orchestration
Workflow Automation
Model Fine-tuning
Data Preparation
API Integration

Location

City of London, England, United Kingdom

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