At a Glance
- Tasks: Build and deploy AI applications using cutting-edge technology and frameworks.
- Company: Early-stage, venture-backed AI start-up with a dynamic team.
- Benefits: Competitive salary, meaningful equity, and hands-on experience.
- Other info: Fast-paced environment with opportunities for rapid career growth.
- Why this job: Shape the future of AI products and make a real impact from day one.
- Qualifications: Strong software engineering skills and experience with AI systems.
The predicted salary is between 50000 - 60000 € per year.
Location: Reading
Compensation: Competitive salary + meaningful equity
Stage: Early-stage, venture-backed AI start-up
Team: Working directly with founders and early engineering team
Overview
We’re building AI-powered products that solve complex real-world problems using large language models and modern machine learning systems. As a founding engineer, you’ll help turn cutting-edge AI capabilities into scalable, reliable products used by real customers. You’ll work across AI systems, backend infrastructure, APIs, and deployment, shaping both the product and technical direction from day one. We’re looking for pragmatic builders who can move from prototype to production fast.
Key Responsibilities
- Build and deploy AI-powered applications using modern LLM APIs and open-source models
- Develop scalable backend systems using Python, FastAPI, TypeScript, Node.js, PostgreSQL, and cloud-native tooling
- Work with AI orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or similar tooling
- Build retrieval and search systems using embeddings, vector databases, and RAG pipelines
- Deploy and manage AI infrastructure using Docker, Kubernetes, Terraform, AWS/GCP, and CI/CD pipelines
- Implement evaluation, monitoring, and observability systems for production AI applications
- Optimise inference performance, latency, caching, and cost efficiency across AI workloads
- Integrate AI systems into customer workflows, internal tooling, and external APIs
- Collaborate closely with founders, product teams, and users to rapidly ship high-impact features
- Own systems end-to-end from architecture through deployment and operational support
- Strong software engineering fundamentals across backend systems, APIs, and cloud infrastructure
- Hands-on experience working with LLMs, embeddings, prompt engineering, or AI product development
- Bonus if you’ve worked in start-ups, developer platforms, data infrastructure, or applied ML environments
Next Steps
If this sounds like your kind of challenge, we’d love to hear from you. The process is designed to move quickly and give you real exposure to the team, technical problems, and opportunity:
- Introductory conversation with the hiring managers / founders
- Collaborative Conversation around product, scaling, and engineering approach
AI Engineer in Reading employer: Experis
As an early-stage, venture-backed AI start-up located in Reading, we offer a dynamic work environment where innovation thrives and every team member plays a crucial role in shaping the future of AI technology. Our culture fosters collaboration with founders and a talented engineering team, providing ample opportunities for personal and professional growth while working on impactful projects that address real-world challenges. With competitive compensation and meaningful equity, we are committed to rewarding our employees as they contribute to building cutting-edge AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer in Reading
✨Tip Number 1
Network like a pro! Reach out to people in the AI space, especially those who work at start-ups. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI and machine learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding AI concepts. Practice common interview questions and consider mock interviews to build your confidence before facing the real deal.
✨Tip Number 4
Don’t forget to 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 and contributing to our exciting projects.
We think you need these skills to ace AI Engineer in Reading
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the AI Engineer role. Highlight any relevant projects or technologies you've worked with, especially those mentioned in the job description.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and how your background makes you a great fit for our team. Be genuine and let your personality shine through!
Showcase Your Projects:If you've built any AI applications or worked on relevant projects, include links or descriptions in your application. We love seeing practical examples of your work and how you approach problem-solving.
Apply Through Our Website:For the best chance of getting noticed, make sure to apply directly through our website. It helps us keep track of applications and ensures you’re considered for the role quickly!
How to prepare for a job interview at Experis
✨Know Your AI Stuff
Make sure you brush up on the latest in AI, especially around large language models and machine learning systems. Be ready to discuss your hands-on experience with LLMs, embeddings, and any relevant projects you've worked on.
✨Show Off Your Coding Skills
Since this role involves building scalable backend systems, be prepared to demonstrate your coding skills in Python, FastAPI, or TypeScript. Practise coding challenges that focus on backend development and APIs to showcase your technical prowess.
✨Understand the Start-Up Culture
As an early-stage venture-backed start-up, they’ll want someone who can adapt quickly. Familiarise yourself with the dynamics of start-ups and be ready to discuss how you can contribute to a fast-paced environment and help shape the product from day one.
✨Prepare for Collaborative Conversations
Expect to engage in discussions about product scaling and engineering approaches. Think about how you can collaborate effectively with founders and product teams, and come prepared with ideas on integrating AI systems into customer workflows.
