
Data Science AI Engineer - RAG Chatbot LangGraph exp
INTEC SELECT LIMITEDData Science AI Engineer - RAG Chatbot LangGraph exp
- London - Hybrid.
- Circa £500 – £675 per day (and negotiable DOE)
- Contract (Outside IR35)
- Agentic AI / Machine Learning.
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:
- 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
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
Opens the company's application page
Listed via
Reed
reed.co.uk
Similar roles
Design & Tech
Related reads from TCHNX

The Inference Economy: Why AI’s Biggest Cost Shift Is Happening After Training
A major shift in AI economics is reshaping the industry. As training frontier models becomes more expensive and inference becomes dramatically cheaper, companies are being forced to rethink how they build, deploy, price, and monetise intelligent systems.

The Emergence of Small Language Models: Why Efficiency Is Overtaking Scale
As the AI industry confronts computational costs and environmental concerns, a new generation of compact models is proving that bigger isn't always better. Small language models are reshaping enterprise AI deployment.

Algorithmic Bias in Design Systems: Why Your AI-Generated UI Might Exclude Users
As AI tools increasingly generate interface components, they're embedding biases that systematically exclude users. Understanding how machine learning models inherit prejudice is essential for creating truly inclusive design systems.

