At a Glance
- Tasks: Lead AI architectural decisions and ensure quality in early-stage AI projects.
- Company: Join a pioneering crypto company focused on making digital assets safer.
- Benefits: Hybrid work, £500 remote budget, $1,000 learning budget, and 25 days holiday.
- Other info: Exciting growth opportunities in a collaborative and innovative team.
- Why this job: Shape the future of AI in a dynamic environment with real impact.
- Qualifications: Experience in AI architecture and strong technical influence without formal authority.
The predicted salary is between 80000 - 100000 £ per year.
The impact you will have:
As Staff AI Engineer, you will be one of the most impactful early hires in Elliptic's next stage of AI expansion. You will join at a moment when Elliptic is actively forming its approach to AI foundations: tooling decisions are being made, agentic patterns are being established, and the kernel of a centralised AI platform is being laid out. Your role is to govern the quality and coherence of those decisions before they crystallise.
You will initially work across our AgentForce and Investigations & AI teams, holding the architectural bar on tooling evaluations, keeping the stack decision open and well-reasoned, and ensuring that the internal agentic patterns being developed today are genuinely inheritable by the customer-facing AI products of tomorrow. You will act as a strong advocate for AI adoption, AI technical best practices, and AI enablement across product, engineering, and development.
This is a role for someone who is comfortable with ambiguity, energised by the challenge of making decisions that others will build on for years, and confident enough to hold a strong technical position without needing a team beneath them to do it.
What you will do:
- Serve as the architectural conscience for Elliptic's early AI decisions, evaluating our current tooling explorations against the requirements of production-scale, customer-facing AI products, and producing a clear, evidence-based recommendation.
- Work consultatively with the Investigations & AI technical lead and AgentForce engineering to ensure that internal agentic patterns, prompt architectures, and evaluation frameworks are being designed with customer-facing scale and regulatory auditability in mind.
- Hold the AI stack decision open responsibly: document trade-offs, establish evaluation criteria, and prevent pragmatic local choices from defaulting the answer before the right person is in place to make it.
- Define and uphold engineering standards for AI systems across the organisation: model observability and tracing, prompt versioning and registry, cost governance, evaluation harnesses, and agent reliability patterns.
- Produce the technical foundation documents that will be a coherent architectural position, a clear view of decisions made and decisions deferred, and an honest assessment of what the architecture can accomplish.
You will be a great fit here if you:
- Are energised by the challenge of bringing rigour to early-stage technical decisions, and understand that preventing a bad architectural choice is often more valuable than shipping a feature.
- Can hold a strong, well-reasoned technical position without needing formal authority to make it stick. You influence through clarity, evidence, and the quality of your thinking.
- Think about AI infrastructure the way the best platform engineers think about data infrastructure: as a set of foundations with internal customers whose needs must be understood and balanced.
- Are comfortable operating in ambiguity and working across teams without a fixed mandate, and know how to make yourself useful in a way that doesn't create dependency or territorial friction.
- Care about the trustworthiness of AI systems, not just their capability. Understand why explainability, auditability, and reliability matter especially in a regulated compliance context.
Our ideal candidate has:
- Made production AI architectural decisions, including evaluation framework selection, LLM integration patterns, prompt management and versioning at scale, and model observability.
- Worked across the boundary between internal tooling and customer-facing AI products, and understands how requirements differ across those contexts, particularly in relation to reliability, auditability, and cost.
- Built or significantly shaped an AI evaluation or observability framework in a production environment, and has strong opinions on what good looks like.
- Operated effectively without a team beneath them. As a Staff IC whose impact comes from technical leadership and cross-team influence rather than people management and team workstream prioritisation.
Bonus Points for:
- Experience building agentic systems in a production context, including orchestration patterns, tool use, memory management, and agent reliability at scale.
- Familiarity with one of the major AI ecosystems, such as LangSmith, MLflow, or Databricks ML.
- Having navigated a transition from a scrappy, point-to-point AI integration to a well-engineered, reusable AI platform.
- An interest in the crypto ecosystem and the mission of making digital assets safer and more accessible.
Job Benefits:
- 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.
- $1,000 Learning & Development budget to use on anything (agreed with your manager) that contributes to your growth and development.
- Holidays: 25 days of annual leave + 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.
- Private Health Insurance - we use Vitality!
- Full access to Spill Mental Health Support.
- Life Assurance: cover is for 4 times your salary to your beneficiaries.
- £100 Crypto for you!
- Cycle to Work Scheme.
Staff AI Engineer in London employer: Elliptic
Contact Detail:
Elliptic Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for those interviews! Research the company, understand their AI products, and be ready to discuss how your experience aligns with their needs. Practise common interview questions and have your own questions ready to show your interest.
✨Tip Number 3
Showcase your skills! Create a portfolio or GitHub repository that highlights your AI projects and architectural decisions. This gives you a chance to demonstrate your expertise and thought process beyond just a CV.
✨Tip Number 4
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 being part of our team at Elliptic.
We think you need these skills to ace Staff AI Engineer in London
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 how energised you are by the challenges of AI architecture and decision-making. Share specific examples of your past experiences that highlight your passion and expertise.
Be Clear and Concise: We appreciate clarity in communication, so make sure your application is easy to read. Avoid jargon unless it's necessary, and get straight to the point. Highlight your key achievements and skills that align with the role without waffling on.
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific requirements of the Staff AI Engineer role. Mention relevant projects or experiences that demonstrate your fit for our team and the impact you can have.
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 it gets the attention it deserves. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Elliptic
✨Know Your AI Foundations
Before the interview, brush up on the key AI concepts and tools mentioned in the job description, like LangSmith and Databricks. Be ready to discuss how these tools can impact architectural decisions and customer-facing products.
✨Showcase Your Decision-Making Skills
Prepare examples from your past experiences where you made significant architectural decisions. Highlight how you evaluated trade-offs and documented your thought process, as this will demonstrate your ability to govern quality and coherence in AI tooling.
✨Embrace Ambiguity
Since the role involves navigating uncertainty, think of scenarios where you've thrived in ambiguous situations. Share how you approached these challenges and made impactful decisions without a fixed mandate.
✨Focus on Trustworthiness
Be prepared to discuss why explainability, auditability, and reliability are crucial in AI systems, especially in regulated environments. Show that you care about building trustworthy AI solutions, not just capable ones.