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We are looking for an AI Systems Architect/Head of AI to own the design, build and deployment of AI systems across the business. This is an implementation-focused role for someone who can translate operational, commercial and trading challenges into working, production-grade solutions. This is not an advisory or strategy-only position. The successful candidate will be hands-on, building systems end to end while operating as a senior technical and commercial leader within the business. The ideal profile is a highly capable senior software engineer with 8 to 20 years of experience building production systems at scale, who has spent the last several years moving deeply into AI and LLM-based systems. AI is now their primary focus, but their credibility comes from engineering excellence and a track record of delivering complex systems in commercially demanding environments.
Job Responsibility
Own the architecture and deployment of AI systems across the business, including model selection, tooling, infrastructure and integration with core business systems
Work closely with the CEO and senior leadership team to identify high-impact AI opportunities across operations, trading and commercial functions
Design, build and deploy AI solutions from prototype through to production, including prompt engineering, data pipelines, evaluations, integrations and operational rollout
Provide engineering capability across the algorithmic trading and software development estate, including building, deploying and supporting trading algorithms, internal tooling and development systems
Hire, lead and grow a high-performing technical team
Operate as a peer to the senior leadership team, translating technical capability into commercial outcomes and owning key architectural and implementation trade-offs
Ensure AI systems are robust, scalable, measurable and commercially effective
Requirements
15 to 20 years of experience building and operating production software systems at scale
Demonstrable experience delivering multiple successful production systems in commercially demanding environments
1 to 3 years of hands-on experience with LLM-based systems, including agentic workflows, RAG architectures, evaluations, integrations and fine-tuning
Strong software engineering capability across the full stack, with deep understanding of production infrastructure and deployment
Experience leading and scaling small technical teams
Commercial fluency and the ability to engage effectively with senior business leadership
Remains highly hands-on technically, capable of coding, debugging, prompting, evaluating and deploying systems directly
Comfortable operating within industrial, asset-intensive or operationally complex businesses