At a Glance
- Tasks: Lead AI architecture decisions and collaborate on innovative blockchain intelligence projects.
- Company: Join a pioneering tech firm focused on blockchain and AI solutions.
- Benefits: Flexible hybrid work, generous leave, health insurance, and learning budgets.
- Other info: Exciting opportunity for growth in a dynamic web3 environment.
- Why this job: Shape the future of AI in blockchain while making a real impact.
- Qualifications: Experience in AI architecture and strong communication skills required.
The predicted salary is between 80000 - 100000 £ per year.
Elliptic develops blockchain intelligence technology that helps financial institutions, regulators, and law enforcement agencies identify financial crime and manage digital asset risk. This Staff AI Engineer position joins the company during a foundational phase of AI platform development, where key architectural decisions, agentic workflows, evaluation frameworks, and observability standards are being established. The role operates across multiple engineering initiatives, helping define scalable AI infrastructure, governance frameworks, and production-ready patterns that support customer-facing AI products. Working closely with engineering and product teams, the successful candidate will influence long-term AI strategy, platform standards, and blockchain infrastructure roles while ensuring reliability, auditability, and operational excellence across AI systems.
Responsibilities:
- Act as the architectural authority for early-stage AI platform decisions and technology evaluations.
- Assess tooling ecosystems, including LangSmith and Databricks, against the requirements of production-scale AI products and provide evidence-based recommendations.
- Collaborate with Investigations & AI and AgentForce engineering teams to ensure agentic architectures and evaluation frameworks are designed for customer-facing scale.
- Maintain an objective and documented AI stack evaluation process, including trade-offs, decision criteria, and architectural considerations.
- Define and promote engineering standards for AI systems, including observability, tracing, prompt management, version control, cost governance, evaluation frameworks, and agent reliability.
- Produce technical foundation documents that clearly outline architecture decisions, deferred considerations, and system capabilities.
- Advocate for AI adoption, engineering best practices, and enablement across product and engineering functions.
Requirements:
- Experience making production AI architecture decisions involving evaluation frameworks, LLM integration strategies, prompt management, versioning, and observability.
- Ability to assess technical trade-offs and guide long-term architectural direction using evidence-based decision-making.
- Experience working across internal tooling platforms and customer-facing AI products.
- Strong understanding of reliability, auditability, governance, and cost considerations in production AI systems.
- Experience designing or significantly influencing AI evaluation or observability frameworks in production environments.
- Ability to operate effectively as an individual contributor with influence driven through technical leadership rather than people management.
- Strong communication skills with the ability to align stakeholders around architectural decisions.
- Comfortable working across teams in environments with evolving requirements and ambiguity.
- Understanding of explainability, trustworthiness, reliability, and compliance requirements within AI systems.
Bonus Points:
- Experience building production-grade agentic systems, including orchestration frameworks, tool integration, memory management, and reliability mechanisms.
- Familiarity with AI ecosystems such as LangSmith, MLflow, Databricks ML, or similar platforms.
- Experience leading the transition from isolated AI integrations to centralized AI platform architectures.
- Understanding of organizational and technical challenges associated with AI platform adoption.
- Interest in cryptocurrency, blockchain technology, and digital assets.
Compensation & Benefits:
- Hybrid work model.
- Work-from-almost-anywhere flexibility for up to 90 days annually.
- £500 remote working budget for home office setup.
- $1,000 annual Learning & Development budget.
- 25 days annual leave plus bank holidays.
- Additional birthday leave day.
- Enhanced parental leave with 16 weeks fully paid leave for eligible employees.
- Private health insurance through Vitality.
- Access to Spill Mental Health Support.
- Life assurance coverage equal to four times salary.
- £100 cryptocurrency benefit.
- Cycle to Work Scheme.
Staff AI Engineer — AI Architecture in London employer: ArtOfBlockchain
Elliptic is an exceptional employer that fosters a collaborative and innovative work culture, particularly for those in the AI engineering field. With a hybrid work model and generous benefits such as a £500 remote working budget, a $1,000 annual Learning & Development budget, and enhanced parental leave, employees are empowered to grow both personally and professionally. The company's commitment to building a strong foundation in AI architecture within the rapidly evolving blockchain space makes it an exciting place for talented individuals seeking meaningful and impactful work.
StudySmarter Expert Advice🤫
We think this is how you could land Staff AI Engineer — AI Architecture in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Elliptic or similar companies. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio or any projects related to AI architecture, make sure to highlight them. Share links during interviews or on your LinkedIn profile to catch their eye.
✨Tip Number 3
Prepare for those tricky questions! Brush up on your knowledge of AI systems, blockchain tech, and production environments. Being able to discuss these topics confidently will set you apart from the crowd.
✨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 joining the team at Elliptic.
We think you need these skills to ace Staff AI Engineer — AI Architecture in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with AI architecture and production systems. We want to see how your skills align with our needs, so don’t hold back on showcasing relevant projects!
Showcase Your Technical Skills:When applying, be specific about the tools and frameworks you’ve worked with, like LangSmith or Databricks. We’re keen to know how you’ve used these in real-world scenarios, so give us the details!
Communicate Clearly:Strong communication is key for this role. In your application, make sure to express your ideas clearly and concisely. We want to see how you can align stakeholders around architectural decisions, so let your writing reflect that!
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 – just follow the prompts!
How to prepare for a job interview at ArtOfBlockchain
✨Know Your AI Architecture Inside Out
Make sure you’re well-versed in the key architectural decisions and evaluation frameworks relevant to production-scale AI products. Brush up on your knowledge of tools like LangSmith and Databricks, as being able to discuss their pros and cons will show you’re ready to make evidence-based recommendations.
✨Showcase Your Collaboration Skills
This role involves working closely with various teams, so be prepared to discuss how you've successfully collaborated in the past. Share specific examples of how you’ve influenced architectural decisions or worked across teams to achieve a common goal, especially in environments with evolving requirements.
✨Demonstrate Your Decision-Making Process
Be ready to explain your approach to assessing technical trade-offs and guiding long-term architectural direction. Use real-life scenarios to illustrate how you’ve made decisions based on evidence and documented processes, highlighting your understanding of reliability and governance in AI systems.
✨Communicate Clearly and Effectively
Strong communication skills are crucial for this position. Practice articulating complex ideas simply and clearly, especially when discussing architectural decisions. Be prepared to align stakeholders around your proposals, showcasing your ability to advocate for AI adoption and engineering best practices.
