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For Companies At a Glance
- Tasks: Build and launch real AI products that impact customers directly.
- Company: Join a leading AI product incubator with strong backing.
- Benefits: Competitive salary, hybrid work, and significant cash bonuses.
- Other info: Fast-paced environment perfect for builders and innovators.
- Why this job: Own your projects from day one and see immediate results.
- Qualifications: 5+ years in full-stack engineering with AI product experience.
The predicted salary is between 140000 - 160000 £ per year.
London | Hybrid (3 days onsite) | £140K – £160K base | OTE £280K – £320K (100% cash bonus + carry)
Build AI products that actually ship. This is not a research lab. This is not a proof-of-concept environment. This is where AI products get built, shipped, and used by real customers. You’ll join a global AI product incubator backed by one of Europe’s leading software investors ($100B+ AUM), building and launching AI products directly inside established B2B businesses. You move fast. You ship. You see the result. Every product has existing customers, real distribution and immediate commercial impact.
What We’re Looking For (Non-Negotiables)
- Experience shipping products at scale from 0 to 1
- 5+ years of experience as a full-stack engineer with strong AI application exposure
- Comfortable across the full stack (infra, backend, frontend)
- Enthusiasm about AI, from the products being built to AI-first ways of working
- Recently built customer-facing AI products (not internal tooling) using LLMs, agentic frameworks, or RAG (within the last 1–2 years)
- Experience working directly with customers and stakeholders
- Experience with enterprise B2B software
The Role
- You will own end-to-end development of AI products, from idea to production.
- Build and launch AI-powered products used by real customers.
- Work across the full stack: backend, frontend, infrastructure, and AI.
- Integrate LLMs and modern AI systems into production environments.
- Make decisions with speed and imperfect information.
- Iterate quickly based on real-world usage and feedback.
- This is a builder role. Not a support function.
What You’ll Work With
- Python, FastAPI
- React, TypeScript
- Kubernetes
- AWS or GCP
- LLMs, GenAI, modern ML frameworks
Why This Role
- Build real AI products, not demos.
- Work at startup speed with institutional backing.
- Own what you build from day one.
- See direct commercial impact of your work.
- Operate like a founder, without taking founder risk.
Who This Is For
- Engineers who want to:
- Build from 0 to 1, repeatedly.
- Work on AI that actually gets used.
- Move fast, take ownership, and ship.
If you’re looking for comfort, this isn’t it. If you want to build, this is exactly it. Click APPLY.
AI Product Engineer in London employer: talentcentric.com
Contact Detail:
talentcentric.com Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Product Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. The more you engage, the better your chances of landing that AI Product Engineer role.
✨Tip Number 2
Showcase your projects! Create a portfolio that highlights your experience shipping products at scale. Include customer-facing AI products you've built recently, and make sure to explain your role in each project.
✨Tip Number 3
Prepare for interviews by practising common questions related to full-stack development and AI applications. Be ready to discuss your thought process when building products from 0 to 1 and how you handle feedback.
✨Tip Number 4
Apply through our website! We want to see your application directly, so don’t hesitate to hit that 'Apply' button. It’s your chance to show us why you’re the perfect fit for this builder role.
We think you need these skills to ace AI Product Engineer in London
Some tips for your application 🫡
Show Your Passion for AI: Let us see your enthusiasm for AI in your application! Share specific examples of AI products you've built or worked on recently. We want to know how you’ve contributed to real-world applications, not just theoretical projects.
Highlight Your Full-Stack Experience: Make sure to showcase your full-stack engineering skills. We’re looking for someone comfortable across the entire stack, so mention your experience with backend, frontend, and infrastructure. Don’t forget to include any relevant technologies like Python, React, or cloud services!
Emphasise Customer Interaction: Since this role involves working directly with customers, highlight any experience you have in that area. Talk about how you’ve gathered feedback and iterated on products based on real user needs. We love engineers who can connect with users!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and get to know you better. Don’t miss out on the chance to join our team and build amazing AI products!
How to prepare for a job interview at talentcentric.com
✨Know Your AI Products
Make sure you’re well-versed in the latest AI products and technologies, especially those that have been built for real customers. Be ready to discuss your experience with LLMs and how you've integrated them into customer-facing applications.
✨Showcase Your Full-Stack Skills
Prepare to demonstrate your full-stack engineering capabilities. Brush up on your knowledge of Python, FastAPI, React, and cloud services like AWS or GCP. Be ready to share specific examples of projects where you’ve worked across the entire stack.
✨Emphasise Speed and Agility
This role is all about moving fast and shipping products. Be prepared to talk about times when you made quick decisions with limited information and how you iterated based on user feedback. Highlight your ability to adapt and pivot as needed.
✨Engage with Stakeholders
Since this position involves working directly with customers and stakeholders, think of examples where you’ve successfully collaborated with them. Show that you understand their needs and can translate that into actionable product features.