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Intec Select

Data Science AI Engineer - RAG Chatbot LangGraph exp

London
£600 – £650/day
Posted about 22 hours ago
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Data Science AI Engineer - RAG Chatbot LangGraph exp

Location: London - Hybrid.
Rate: Circa £600 – £650 per day (and negotiable DOE)
Type: Contract (Outside IR35)

Company:

Our client is a globally established B2B information and professional services business, operating across multiple high-value industry sectors. They have established data science and machine learning engineering teams already delivering in production, and are now expanding their AI capability significantly across the global organisation.

This is a high-impact role with strong visibility across the organisation, working closely with product managers, engineers, and other data scientists to design and deploy AI, agentic and chatbot solutions that improve the quality of our products and automate complex workflows.

You’ll have the opportunity to work across the full lifecycle of data science: exploration, modelling, experimentation, and production deployment — while contributing to systems used by global.

What you'll be working on as Data Science AI Engineer - RAG Chatbot LangGraph exp:

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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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.

  • AI Agents powered by LLMs and advanced RAG/Agentic architectures.
  • LLM Chatbots that support user’s queries through automated search, content ranking and marketing campaigns evaluation.
  • Smart Data Agents that interpret and summarise time series data.
  • MCP Servers that allow internal and external services to securely interact with tools, APIs and databases.
  • You’ll have the autonomy to explore ideas, prototype new features, and collaborate with engineering teams to ship production-ready solutions.
  • Build and deploy Chatbots, MCP Servers and Agentic models for our SaaS platforms.
  • Collaborate with product and engineering teams to productionise models and pipelines.
  • Contribute high-quality code to GitHub-based workflows and peer review processes.
  • Validate model performance and maintain high standards for data and model accuracy.
  • Communicate insights and technical solutions clearly to technical and non-technical stakeholders.

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You're experience as Data Science AI Engineer - RAG Chatbot LangGraph exp:

Core Skills:

  • Strong Python and SQL skills – We want people who write clean code (using AI assistant coding is fine, but we want people that understand the language and can explain why they went with a certain approach).
  • Experience building chatbots powered by RAG pipelines.
  • Experience with LangGraph for agentic frameworks.
  • Experience working with large, real-world datasets.
  • Familiarity with cloud environments such as AWS, GCP, or Azure.
  • Experience working in collaborative software environments using Git.

A candidate will likely have:

  • Exposure to recommendation systems or time-series forecasting.
  • Solid understanding of ML models beyond “from sklearn import …”.
  • A Masters or higher in a quantitative discipline (Statistics, Maths, Computer Science, Economics, etc.).

Nice to have:

  • A mentorship mindset.
  • Ability to work under tight deadlines and with minor supervision.
  • MCP Servers experience.
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Skills

Python
SQL
Chatbots
RAG Pipelines
LangGraph
Machine Learning
Data Science
Cloud Environments
Git
Recommendation Systems
Time-Series Forecasting
Data Accuracy
MCP Servers
Data Interpretation
Data Summarization

Location

London, England, United Kingdom

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