Hyperlayer
AI Engineer

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We’re Growing Our AI Team 🚀
Hyperlayer is on a mission to reinvent how people and businesses move money, and we need a mid-level AI Engineer with big ideas to help us make it happen. This isn’t just about writing code; it’s about building the AI infrastructure for the future of payments.
You’ll dive into projects like real-time conversational AI, agentic commerce, and next-gen personalisation. If you love solving hard problems and turning wild ideas into reality, you’ll fit right in.
What You’ll Do
- Build AI-powered features for our platform, including intelligent interfaces, agentic workflows and effortless automation
- Partner with product, engineering and business teams to identify high-value AI opportunities and grow adoption through shared practices and reusable patterns
- Help cross-functional teams organise structured and unstructured knowledge bases through GenAI techniques such as Retrieval Augmented Generation (RAG), enabling quick and accurate search with robust access controls
- Connect AI applications and agents securely to enterprise data and tools using APIs, tool calling and emerging interoperability standards
- Evaluate open-source and managed AI technologies, balancing developer experience, model quality, security, reliability, data residency and cost
- Turn promising experiments into scalable, reliable and secure production capabilities, and help shape Hyperlayer’s AI roadmap
You should apply if you have:
- 2-3 years’ experience building and deploying AI/ML or LLM applications, ideally with the controls expected in regulated industries
- Strong Python and SQL skills and experience with LLM frameworks such as LangChain
- Hands-on experience with LLMs and generative AI, including prompt and context engineering
- Experience building knowledge retrieval or search solutions using RAG, embeddings or vector databases
- Experience connecting AI applications to enterprise systems and data through APIs, tool calling or similar integration patterns
- Comfort with cloud platforms (AWS mainly, GCP is a plus) and container technology (Docker, Kubernetes)
- Ability to evaluate AI tools and models across quality, latency, reliability, security and cost
- Understanding of access controls, data privacy and secure AI workflows
- Strong communication, facilitation and cross-functional collaboration skills
- A curious, data-driven approach to experimentation, learning and turning prototypes into production
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Bonus Points For
- Experience building internal technical communities or supporting organisation-wide AI adoption
- Familiarity with agent and agentic protocols such as Agent-to-Agent, Model Context Protocol and Agent-to-Payments
- Experience integrating AI with enterprise data platforms, data warehouses or file repositories
- Hands-on experience with vector databases and evaluation approaches for RAG pipelines
- Familiarity with open-source coding agents, developer tools or AI orchestration frameworks
- Experience deploying or consuming LLM endpoints in cloud environments with data residency requirements
- Knowledge of LLM evaluation, observability, fine-tuning or AI cost optimisation
- Understanding of security, privacy, bias and safety considerations in AI systems
(You don’t need every skill. If you’re passionate about building the future with AI, we want to hear from you.)
How to apply
Please click on the ‘Apply’ button, you will be asked to provide an updated CV and answer some questions. For further information about this vacancy, you can contact us at: people@hyperlayer.com. We will not be offering UK work visa sponsorship for these roles. Candidates will need an existing non-sponsored right to work in the UK.


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Working at Hyperlayer
At Hyperlayer we are proud of our in-office culture. It makes a real difference to the working atmosphere and maximises collaboration in and across teams. This is critical to how we work and learn. Also, we think it makes for a great workplace!
We value our team and are proud to offer some great benefits:
- A performance-based employee bonus scheme.
- 25 days annual leave plus bank holidays, a day off on your birthday, and an additional day per year of tenure to a maximum of 30.
- Critical illness and life insurance cover.
- AXA PPP Health Insurance, including gym offers.
- Cycle-to-work scheme.
- Referral bonus scheme.
- Workplace Nursery Scheme
Equity, diversity, and inclusion
Hyperlayer’s mission is to make a positive impact on people’s lives, making it easier for everyone to manage their money.
Hyperlayer’s commitment to equity, diversity, and inclusion is a key part of this; it helps us better serve our customers, employees, and business partners from every background.
We are constantly learning and striving to do better, and we expect all staff to actively take part in this process.
Data Privacy
As part of our recruitment process, Hyperlayer Limited collects and processes personal data relating to job applicants. We are committed to being transparent about how we collect and use this data and to meeting our data protection obligations. To read more click here.
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