At a Glance
- Tasks: Build innovative AI solutions that enhance user learning experiences.
- Company: Join a pioneering AI coaching platform in a hybrid work environment.
- Benefits: Competitive salary, equity package, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on risk-taking and innovation.
- Why this job: Be at the forefront of AI technology and make a real impact.
- Qualifications: Expertise in AI, Python, and modern AI stacks required.
The predicted salary is between 50000 - 55000 € per year.
Location: London (Hybrid – around 2 days a week in the office)
Salary: £50k to £55k, based on experience
Our AI coaching platform replicates the coaching of 9 of the world’s top experts. We’re looking for an AI Engineer with exceptional capabilities seeking to make real-time augmentation a reality. Someone who likes to punch above their weight and is excited by the idea of building the 1st ever learning tool with 100% active users.
Are you an AI expert? We’re looking for an AI expert who finds agent architectures exciting, stays up to date with the latest LLMs and can design novel experiences. You understand users, and love owning features end-to-end: from product thinking and technical design to shipping polished experiences.
Last but not least, this role is for risk-takers only. Architect and optimize the end-to-end AI lifecycle, from data ingestion to inference. Iterate on model accuracy and retrieval performance using systematic evaluation frameworks.
- Build out our AI experiences — things like RAG pipelines, multimodal user experiences, and LLM-powered experiences that actually work in production.
- Implement AI-specific security and privacy guardrails, including PII redaction and prompt injection mitigation.
- Optimize inference latency and token costs to ensure our AI features are both snappy and sustainable.
- Deep technical expertise in the modern AI stack (LangChain/LlamaIndex, DSPy, or similar).
- Mastery of Python and asynchronous programming, with a focus on building high-performance AI backends.
- Experience working with LLMs, vector databases, and retrieval-augmented generation (RAG).
- Strong understanding of embedding models, rerankers, and hybrid search.
- Hands-on experience deploying AI systems in production.
- Experience in dealing with IT audits with prospects.
- A good grasp of cloud infrastructure (Azure, AWS, or GCP).
- A curiosity for how people learn and grow — and how tech can help with that.
You’ll get to work with cutting-edge AI tech — not just talk about it. You’ll share the risks and rewards - the compounding equity package will reflect that.
If you love the idea of building an AI product that actually helps people — and you want to be there from the start, helping shape both the tech and the culture — we’d love to chat.
AI engineer employer: Ignitus
At Ignitus, we pride ourselves on being an innovative employer that fosters a dynamic and collaborative work culture. Our hybrid model allows for flexibility while working in the vibrant city of London, and we offer competitive salaries alongside a compounding equity package that rewards your contributions. With a strong focus on employee growth, you'll have the opportunity to work with cutting-edge AI technology and shape the future of learning tools, all while being part of a team that values creativity and risk-taking.
StudySmarter Expert Advice🤫
We think this is how you could land AI engineer
✨Tip Number 1
Network like a pro! Reach out to people in the AI field, attend meetups, and connect with professionals on LinkedIn. 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 or RAG pipelines. 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. Be ready to discuss your experience with Python, cloud infrastructure, and AI systems. Practice common interview questions to boost your confidence!
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in our mission. Tailor your application to highlight how your skills align with our vision of building an AI product that truly helps people.
We think you need these skills to ace AI engineer
Some tips for your application 🫡
Show Your Passion for AI:When you're writing your application, let your enthusiasm for AI shine through! We want to see that you’re not just an expert but also genuinely excited about building innovative solutions that help people learn and grow.
Tailor Your Experience:Make sure to highlight your relevant experience with the modern AI stack and any hands-on projects you've worked on. We love seeing how you've tackled challenges in the past, so don’t hold back on those details!
Be Clear and Concise:While we appreciate creativity, clarity is key! Keep your application straightforward and to the point. Use bullet points if it helps convey your skills and experiences more effectively.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Ignitus
✨Know Your AI Stuff
Make sure you brush up on the latest advancements in AI, especially around LLMs and agent architectures. Be ready to discuss your hands-on experience with deploying AI systems and how you've tackled challenges in production.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've optimised AI features or improved model accuracy. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your impact.
✨Understand User Needs
Since this role is all about creating user-centric experiences, think about how you've previously designed features with the end-user in mind. Be ready to discuss your approach to gathering user feedback and iterating on designs.
✨Be Ready to Take Risks
This position is for risk-takers, so come prepared to talk about a time when you took a calculated risk in your work. Discuss what you learned from that experience and how it shaped your approach to AI development.
