Owns end-to-end delivery of priority IPB AI/ML use cases, from problem framing and business case through to deployed, monitored production services with measurable advisor and client impact
Leads the engineering build of agentic AI and LLM-powered products serving IPB advisors and clients across international markets
Sets the engineering quality bar for the team's AI products through code reviews, technical design, and pairing with peers and junior engineers
Establishes and operates Responsible AI controls in production (guardrails, evaluation frameworks, observability, and model risk controls) to firm-wide standards
Acts as a primary technical partner to IPB business stakeholders, surfacing new AI/ML opportunities and shaping them into funded workstreams
Represents the AIML team in firm-wide AI/ML governance and engineering forums; ensures cross-border, regulatory, and data-privacy considerations are reflected in solution design
Contributes to the team's GenAI education programme through training content, knowledge-sharing sessions, and mentoring of junior engineers and interns
Champions the firm's culture of diversity, Opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
Formal training or certification on AI/ML engineering concepts and applied experience
Advanced proficiency in Python and modern software engineering practices (testing, design patterns, code review, version control)
Fluent with AI coding tools (e.g., Claude Code, GitHub Copilot) as a core part of day-to-day software development, with the judgement to know when to lean on them and when not to
Hands-on experience building, evaluating, and deploying machine learning models into production
Practical experience with Large Language Models, including prompt engineering, RAG, fine-tuning, and agentic frameworks
Practical experience with CI/CD, containerisation, and cloud-native deployment patterns
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