At a Glance
- Tasks: Design and build AI-powered features for crypto compliance tools.
- Company: Join Elliptic, a leader in making crypto markets safer and more transparent.
- Benefits: Enjoy hybrid work, generous leave, and a £1,000 learning budget.
- Other info: Collaborative environment with excellent growth opportunities and a focus on innovation.
- Why this job: Make a real impact in the fast-paced world of cryptocurrency and AI.
- Qualifications: 3-6 years in software engineering with LLM frameworks experience.
The predicted salary is between 60000 - 80000 £ per year.
Elliptic is building AI‑powered tools that help compliance teams investigate crypto transactions faster and with greater confidence. Our Automation Forge team sits at the centre of that work, designing the AI systems and backend services behind Elliptic's copilot, the product that helps investigators trace fund flows, spot patterns, and respond to risk in real time.
As an AI Engineer on the Automation Forge team, you'll build the agentic workflows, evaluation guardrails, retrieval pipelines and supporting services that power Elliptic's copilot and other AI‑driven features. You'll work with product managers, web engineers and your engineering lead to turn complex blockchain data into intelligent, user‑friendly experiences. Your work will help compliance teams trace fund flows, uncover patterns and respond to risk faster and more confidently. Working collaboratively across disciplines, you’ll contribute to impactful features and continuously improve the quality, reliability and usefulness of our AI systems. Through this work, you’ll play an essential role in advancing Elliptic’s mission to make crypto markets safer, more transparent and more efficient.
What You Will Do
- Build and maintain AI‑powered features and agentic workflows that power Elliptic's copilot, using LLM frameworks such as LangChain and LangGraph.
- Design prompts, tool integrations and retrieval pipelines that turn complex blockchain data into useful answers for investigators.
- Develop and run evaluations to measure and improve the quality, reliability and latency of LLM outputs.
- Design and build the backend services, APIs and event‑driven systems that support these features, using TypeScript and Node.js.
- Collaborate with product, domain experts, web engineers and your engineering lead to take features from prototype through to production.
- Take part in technical design reviews, planning and code reviews.
- Care about how your services run in production: observability, cost and reliability of LLM‑based systems.
What You'll Bring
- 3 to 6 years of software engineering experience, with meaningful hands‑on work building LLM‑powered features in production.
- Direct experience with LLM frameworks such as LangChain, LangGraph, LlamaIndex or similar.
- Practical understanding of prompt engineering, tool/function calling, subagents, structured outputs and managing context windows.
- Experience evaluating LLM outputs and iterating on prompts/pipelines, including building eval sets, measuring quality and using observability tools (LangSmith, Langfuse, Arize or similar).
- Strong backend skills in TypeScript / Node.js, with solid API design.
- Cloud experience (AWS: Lambda, ECS, S3 or similar).
- Database proficiency across SQL (Postgres) and some NoSQL exposure.
- Clear thinking about system design and trade‑offs, especially those specific to LLM systems: cost vs latency vs quality, deterministic vs probabilistic behaviour.
- Strong collaboration skills across engineering, product and design.
Nice to Have
- Experience with agentic patterns: planning, multi‑step reasoning, tool use loops.
- Experience working with multiple model providers (Anthropic, OpenAI, open‑weight models).
- Hands‑on Terraform, Kubernetes or infrastructure‑as‑code experience.
- Experience with observability platforms like Datadog (metrics, tracing, alerting).
- Distributed or event‑driven architectures (SNS, SQS, etc.).
- Interest in cryptocurrency, blockchain or compliance, though we’re happy to bring you up to speed.
Job Benefits
How we work
- Hybrid working and the option to work from almost anywhere for up to 90 days per year.
- £500 Remote working budget to set up your home office space.
Learning & Development
- $1,000 Learning & Development budget to use on anything (agreed with your manager) that contributes to your growth and development.
Vacation / Leave
- Holidays: 25 days of annual leave plus bank holidays. An extra day for your birthday.
- Enhanced parental leave: we provide eligible employees, regardless of gender or whether they become a parent by birth or adoption, 16 weeks fully‑paid leave.
Benefits
- Private Health Insurance – we use Vitality.
- Full access to Spill Mental Health Support.
- Life Assurance: we hope you will never need this – but our cover is for 4 times your salary to your beneficiaries.
- £100 Crypto for you.
- Cycle to Work Scheme.
AI Engineer employer: Elliptic
At Elliptic, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. As an AI Engineer, you'll have the opportunity to work on cutting-edge AI-powered tools in a hybrid environment, with generous benefits including a £1,000 learning budget, 25 days of annual leave, and enhanced parental leave. Our commitment to employee growth and well-being, combined with our mission to make crypto markets safer, makes Elliptic a truly rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people 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 AI projects, especially those involving LLM frameworks. 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 technical questions related to AI and LLMs. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission at Elliptic.
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the AI Engineer role. Highlight your experience with LLM frameworks and backend development, as this will show us you’re a great fit for our team.
Showcase Your Projects:Include specific examples of projects where you've built LLM-powered features or worked with TypeScript and Node.js. We love seeing real-world applications of your skills, so don’t hold back!
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to explain your experience and how it relates to the job. We appreciate clarity and want to understand your journey easily.
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’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Elliptic
✨Know Your LLM Frameworks
Make sure you brush up on your knowledge of LLM frameworks like LangChain and LangGraph. Be ready to discuss how you've used these tools in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your Collaboration Skills
Since this role involves working closely with product managers and web engineers, be prepared to share examples of successful collaborations. Highlight how you’ve contributed to team projects and how you handle feedback during code reviews.
✨Demonstrate Your Problem-Solving Abilities
Expect questions that assess your ability to design and build backend services. Prepare to discuss specific instances where you had to make trade-offs between cost, latency, and quality in your system designs.
✨Prepare for Technical Questions
Brush up on your TypeScript and Node.js skills, as well as your understanding of APIs and database management. You might be asked to solve a coding problem or explain your thought process in real-time, so practice articulating your approach clearly.
