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For Companies At a Glance
- Tasks: Design and build AI systems that impact millions of users across various industries.
- Company: High-growth AI scale-up focused on innovative, production-grade solutions.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Why this job: Join a cutting-edge team and shape the future of AI technology.
- Qualifications: Strong software engineering skills and a passion for AI applications.
- Other info: Dynamic environment with real ownership of impactful projects.
The predicted salary is between 60000 - 80000 £ per year.
A high-growth AI and analytics scale-up is building next-generation intelligent systems that help global enterprises better understand and act on customer behaviour at scale. This is an opportunity to join a deeply technical, product-focused engineering team working on real-world, production AI systems — not just prototypes — leveraging LLMs, agentic workflows, and modern cloud infrastructure.
You’ll play a key role in bridging the gap between software engineering and applied AI, building systems that directly impact millions of users across multiple industries.
As an AI Engineer, you’ll design, build, and deploy agent-driven software systems that turn cutting-edge AI capabilities into reliable, scalable products. This is a hands-on, end-to-end role, covering everything from prototyping through to production deployment and iteration.
Key Responsibilities- Build scalable, production-grade agentic systems and AI-powered applications
- Design and develop end-to-end features from concept to deployment
- Develop and maintain data pipelines, APIs, and CI/CD workflows
- Work closely with product and design teams to deliver user-facing functionality
- Apply best practices across performance, scalability, and maintainability
- Contribute to technical discussions, code reviews, and knowledge sharing
- Strong software engineering fundamentals (SDLC, testing, system design)
- Experience taking products from development → production
- Familiarity with cloud infrastructure and deployment pipelines
- Exposure to or strong interest in agentic systems / LLM applications
- Product mindset — focused on impact, iteration, and delivery
- Curious, adaptable, and comfortable working in an evolving AI landscape
- Experience with data pipelines or data engineering
- Understanding of large language models (LLMs) and real-world applications
- Exposure to modern AI tooling, agents, or workflow orchestration frameworks
You’ll work across a modern, AI-first stack including:
- Agent Frameworks: MCP (Model Context Protocol), agent-to-agent systems, emerging agent tooling
- Frontend: TypeScript, React, Next.js
- Backend: Python, Node.js
- Data & ML Platform: Databricks
- Infrastructure: AWS, Docker, Kubernetes
- Build production AI systems at scale (not just experimentation)
- Work on agentic / LLM-first products at the forefront of industry evolution
- Join a high-growth environment with strong technical leadership
- Real ownership across the full lifecycle of AI-powered features
Artificial Intelligence Engineer in London employer: Intent HQ
Contact Detail:
Intent HQ Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the AI and tech space, especially those working at companies you're interested in. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to agentic systems or LLM applications. This gives potential employers a taste of what you can do beyond the written application.
✨Tip Number 3
Prepare for technical interviews by brushing up on your software engineering fundamentals. Practice coding challenges and be ready to discuss your past projects in detail—this is where we can really shine!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Artificial Intelligence Engineer in London
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let your enthusiasm for AI and agentic systems shine through. We want to see that you’re not just looking for a job, but that you’re genuinely excited about building scalable AI solutions that make a difference.
Highlight Relevant Experience: Make sure to showcase any experience you have with software engineering, cloud infrastructure, or LLM applications. We’re looking for candidates who can bridge the gap between software and applied AI, so don’t hold back on sharing your relevant projects!
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured applications that get straight to the heart of your skills and experiences. Avoid jargon unless it’s relevant, and make sure we can easily see how you fit the role.
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 you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Intent HQ
✨Know Your AI Fundamentals
Brush up on your software engineering fundamentals, especially around the software development lifecycle (SDLC), testing, and system design. Be ready to discuss how you've applied these principles in past projects, particularly in taking products from development to production.
✨Showcase Your Cloud Knowledge
Familiarise yourself with cloud infrastructure and deployment pipelines, as this role heavily relies on them. Be prepared to talk about your experience with AWS, Docker, or Kubernetes, and how you've used these tools to build scalable applications.
✨Demonstrate Your Product Mindset
This position values a product-focused approach, so think about how you can convey your understanding of impact, iteration, and delivery. Share examples of how you've contributed to user-facing functionality and worked closely with product and design teams.
✨Engage in Technical Discussions
Be ready to contribute to technical discussions during the interview. This could involve code reviews or sharing insights on agentic systems and LLM applications. Show your curiosity and adaptability by discussing how you stay updated with the evolving AI landscape.