AI Infrastructure Engineer

Elliptic develops blockchain intelligence solutions used by financial institutions, regulators, and law enforcement agencies to improve trust and transparency across digital asset ecosystems. This position joins the newly established AI Platform team, responsible for building the foundational infrastructure that enables AI development across the organization. The role focuses on designing scalable AI systems, model serving infrastructure, prompt pipelines, evaluation frameworks, observability tooling, and agentic workflow capabilities. Working closely with engineering teams across multiple business units, the successful candidate will help establish the platform standards, integration patterns, and operational foundations required to support production AI systems at scale while contributing to blockchain infrastructure roles and AI-driven product development initiatives.

Responsibilities

• Build and maintain core AI platform components including model serving infrastructure, prompt pipelines, evaluation frameworks, and integration patterns.
• Support the development of agentic workflows through orchestration tooling, reliability mechanisms, and platform services.
• Implement observability capabilities for AI systems, including tracing model interactions, monitoring token usage, measuring latency, and tracking quality metrics.
• Contribute to frameworks and tooling that support prompt development, version control, testing, and governance across teams.
• Partner with engineering teams across Real-time Risk, Investigations, Data Fabric, and other domains to support AI integrations.
• Evaluate emerging AI technologies, orchestration patterns, model capabilities, and assessment techniques to determine relevance for the organization.

Requirements

• Strong interest in artificial intelligence, large language models, and emerging AI technologies.
• Ability to design and build infrastructure that supports engineering teams through reliability, documentation, and maintainability.
• Comfortable working in evolving environments with incomplete requirements and changing priorities.
• Strong systems-thinking approach with the ability to evaluate dependencies, scalability, extensibility, and failure scenarios.
• Effective communication and collaboration skills.
• Hands-on experience with LLMs or machine learning systems in professional, academic, or personal projects.
• Familiarity with AI protocols including MCP, A2A, ACP, or similar emerging standards.
• Solid software engineering fundamentals, including maintainable and testable code development.
• Deep understanding of context windows and their impact on agentic workflows, including context management concepts.
• Experience or exposure to at least one of the following areas: API integration and orchestration, Data pipeline development, Model evaluation and testing, Observability and monitoring systems.
• Demonstrated learning mindset and ability to adapt to rapidly changing technologies.

Bonus Points

• Experience with LLM and agentic frameworks such as LangChain, LangSmith, Databricks AgentBricks, or similar platforms.
• Experience in prompt engineering, evaluation dataset creation, or LLM output quality assessment.
• Interest in cryptocurrency, blockchain technology, and digital assets.
• Experience working in regulated, compliance-focused, or trust-sensitive environments.
• Familiarity with MLflow, Databricks ML, or other machine learning lifecycle tooling.

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 of 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.