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For Companies At a Glance
- Tasks: Design and optimise AI systems for a personal finance co-pilot, impacting thousands of users.
- Company: Join a fast-paced startup revolutionising personal finance with cutting-edge AI technology.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Why this job: Shape the future of finance with innovative AI solutions and high ownership of your work.
- Qualifications: 3+ years in applied ML/AI engineering and strong Python skills required.
- Other info: Collaborative environment with a focus on compliance and rapid product development.
The predicted salary is between 36000 - 60000 ÂŁ per year.
The company is seeking an AI/ML Engineer to own and evolve the intelligence layer behind Lily. The role works across LLM orchestration, prompt engineering, agentic AI systems, model evaluation, and data pipelines to make the AI co‑pilot faster, safer, and more autonomous. This is a hands‑on, high‑ownership role where the AI/ML Engineer’s work directly shapes the product experience for thousands of users as the company scales across the U.S. market.
What You’ll Do
- Design, build, and optimise the AI planning engine powering Lily, the personal finance co‑pilot.
- Architect and develop agentic AI capabilities – enabling Lily to autonomously execute multi-step financial tasks, make tool calls, and reason across complex user scenarios.
- Develop and maintain LLM orchestration pipelines, including prompt management, context handling, and response quality controls.
- Build automated evaluation and regression testing systems to ensure AI outputs meet U.S. financial regulatory standards (U.S. Securities and Exchange Commission, Financial Industry Regulatory Authority, Investment Advisers Act of 1940).
- Improve model response latency and cost‑efficiency across real-time user interactions.
- Implement retrieval‑augmented generation (RAG) and tool‑use patterns for personalised financial insights.
- Collaborate with product, engineering, and compliance teams to ship AI features safely and quickly.
- Monitor model performance in production and establish retraining/fine‑tuning cadences as data scales.
- Contribute to the architecture for U.S. market expansion, including multi‑jurisdictional compliance logic and cross‑border financial data flows.
What We’re Looking For
- 3+ years of experience in applied ML/AI engineering (not purely academic/research).
- Strong hands‑on experience with LLMs in production: prompt engineering, fine‑tuning, evaluation, and orchestration (e.g. LangChain, LlamaIndex, or custom pipelines).
- Experience designing or building agentic systems – multi‑step reasoning, tool use, planning, and autonomous task execution.
- Proficiency in Python; experience with Django or FastAPI is a plus.
- Practical understanding of RAG architectures, embedding models, and vector databases.
- Experience building evaluation frameworks and automated testing for AI systems.
- Familiarity with cloud infrastructure (GCP preferred) and CI/CD pipelines.
- Strong communicator who can collaborate across engineering, product, and compliance.
- Comfortable working in a fast‑moving startup environment with high autonomy.
- Based in the UK with the ability to work from the London office 3 days per week.
Nice to Have
- Experience in fintech, regtech, or regulated industries.
- Knowledge of U.S. financial regulations (U.S. Securities and Exchange Commission, Financial Industry Regulatory Authority, Securities Investor Protection Corporation, Investment Advisers Act of 1940).
- Experience with OpenAI and/or Anthropic APIs at scale.
- Background in data pipelines and ETL for financial data.
- Experience building autonomous agent frameworks or multi‑agent systems.
- Contributions to open‑source AI/ML projects.
AI/ML Engineer employer: Calyptus
Contact Detail:
Calyptus Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the AI/ML space, especially those who work at companies you're interested in. A friendly chat can open doors and give you insider info on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs or agentic systems. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common AI/ML questions and scenarios. Practice explaining your thought process when tackling complex problems, as this will demonstrate your hands-on experience and problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from candidates who are excited about joining us. Plus, it shows you're genuinely interested in being part of our team.
We think you need these skills to ace AI/ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI/ML Engineer role. Highlight your hands-on experience with LLMs and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how you can contribute to Lily's evolution. Be sure to mention any experience with agentic systems or financial regulations, as these are key for us.
Showcase Your Projects: If you've worked on any cool AI projects, don't hold back! Include links or descriptions of your work, especially if it involves prompt engineering or model evaluation. We love seeing practical applications of your skills!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Calyptus
✨Know Your AI/ML Stuff
Make sure you brush up on your knowledge of LLMs, prompt engineering, and agentic systems. Be ready to discuss specific projects you've worked on, especially those involving multi-step reasoning and tool use. This will show that you have the hands-on experience they're looking for.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled challenges in previous roles, particularly around model evaluation and performance optimisation. Think of examples where you improved response latency or cost-efficiency, as these are key aspects of the role.
✨Familiarise Yourself with Compliance
Since the role involves working with U.S. financial regulations, it’s a good idea to brush up on relevant laws like the Investment Advisers Act of 1940. Being able to discuss how you would ensure compliance in your AI systems will set you apart from other candidates.
✨Collaborate and Communicate
This position requires collaboration across various teams, so be prepared to demonstrate your communication skills. Share examples of how you've successfully worked with product, engineering, and compliance teams in the past to deliver AI features quickly and safely.