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For Companies At a Glance
- Tasks: Build and deploy cutting-edge AI systems that make a real-world impact.
- Company: Join a global leader in AI innovation with a collaborative culture.
- Benefits: Competitive pay, hybrid work model, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement opportunities in a fast-paced environment.
- Why this job: Shape the future of AI and work on high-impact projects that matter.
- Qualifications: Experience with LLMs, AI systems, and strong programming skills required.
Hybrid – London (3 days office - 2 days remote)
Rate: 500-550 Outside IR 35
Contract: 6 months initially
Build Production-Grade AI Systems at Scale
We’re Looking for AI Builders — Not Just Experimenters. If you’ve deployed real-world LLMs, built autonomous AI agents, and engineered scalable AI systems that people actually use, this is the opportunity to shape the future of AI across a global organisation.
We’re building next-generation AI capabilities across both:
- AI-powered SaaS / B2B products
- Enterprise-wide AI transformation initiatives
You’ll work on high-impact systems that automate workflows, enhance decision-making, and deliver measurable business value at scale.
What You’ll Build:
- You’ll design and deploy intelligent AI systems powered by:
- Large Language Models (LLMs)
- Agentic AI frameworks
- Retrieval-Augmented Generation (RAG)
- Multi-agent orchestration
- Tool-using autonomous workflows
This is a hands-on engineering role focused on production delivery, scalability, reliability, and business impact.
Your Work Will Include:
- Building AI agents with reasoning, planning, memory, and tool orchestration
- Developing advanced RAG pipelines and context-aware AI systems
- Designing MCP-style architectures and interoperable AI workflows
- Creating recommendation, forecasting, and classification models on large-scale datasets
- Automating complex business operations using AI-driven decision systems
- Integrating AI into APIs, enterprise platforms, and customer-facing products
- Optimising latency, inference performance, observability, and cost efficiency
What We’re Looking For:
We want engineers and scientists who can take AI from concept to production.
Strong Experience In:
- LLMs, GenAI, and Agentic AI systems
- LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks
- RAG pipelines and vector databases
- AI agents and multi-agent orchestration
- Python, PyTorch, TensorFlow, Scikit-learn
- Cloud AI platforms such as AWS, Azure, or GCP
- Production deployment, MLOps, and scalable AI infrastructure
- API integration and workflow automation
Bonus Points For:
- MCP / Model Context Protocol experience
- Fine-tuning and evaluation frameworks
- Recommendation systems and forecasting models
- Real-world enterprise AI transformation experience
- Experience balancing model quality, latency, and operational cost
Why Join Us?
- Work on AI systems used at global scale
- Join a production-first AI engineering culture
- Build technology that directly impacts products, operations, and business strategy
- Collaborate with strong engineering, product, and data teams
- Influence how enterprise AI is designed and deployed across a global organisation
If you enjoy solving complex problems, deploying real AI systems, and building beyond prototypes, this role offers the opportunity to make a genuine impact.
Data Scientist in City of London employer: Russell Tobin
Contact Detail:
Russell Tobin Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and AI systems. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and approach real-world problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about joining our team!
We think you need these skills to ace Data Scientist in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match our job description. Highlight your work with LLMs, AI agents, and any real-world deployments you've done. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and how your background aligns with our mission. Let us know why you're excited about building production-grade AI systems and how you can contribute to our projects.
Showcase Your Projects: If you've worked on relevant projects, don't hold back! Include links or descriptions of your previous work with AI systems, especially those that demonstrate your ability to deploy scalable solutions. We love seeing practical examples of your skills!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Russell Tobin
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs, GenAI, and Agentic AI systems. Be ready to discuss specific projects where you've deployed these technologies, as well as any frameworks like LangChain or PyTorch that you've used. This will show them you're not just a theorist but someone who can get things done.
✨Showcase Your Problem-Solving Skills
Prepare to talk about complex problems you've solved in previous roles, especially those involving AI systems. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help you clearly demonstrate your impact and how you approach challenges.
✨Get Familiar with Their Tech Stack
Research the tools and platforms mentioned in the job description, like AWS, Azure, or GCP. If you have experience with MLOps or API integration, be ready to share examples of how you've used these in past projects. This shows you're proactive and genuinely interested in the role.
✨Ask Insightful Questions
Prepare thoughtful questions about their AI initiatives and how they measure success. This not only shows your enthusiasm for the role but also helps you gauge if the company aligns with your career goals. Plus, it gives you a chance to engage in a meaningful conversation during the interview.