AI Engineer

Role Overview

This is a newly created Phase 1 opportunity in our Global Broking division for an AI Engineer, joining the firm's new AI Solutions Group. Two engineers are being hired in this phase — one in London and one in New York — to establish the operating model for embedded AI delivery on the broking desks.

Responsibilities

• Embed on assigned pilot desks in London or New York — sit with brokers, understand their workflow, and identify areas that are slow, repetitive or error-prone, as well as opportunities where AI changes what is possible.
• Architect, design and build production-grade AI solutions — including Generative AI and agentic capabilities — that remove friction from the broking workflow and unlock new ways of working across idea generation, research, pricing, execution, booking and post-trade.
• Deliver every solution through the firm's agreed safe route to production — covering security, compliance, model risk, change management, audit and operational ownership in production — with zero ad-hoc exceptions.
• Contribute to and reuse from the shared AI capability library — check existing capabilities before building new ones, and place everything you build into the library so other desks and regions can adopt it without rebuilding.
• Co-develop the team's shared platforms, frameworks and components with peers in the AI Solutions Group and the wider Technology organisation, customising for domain-specific desk requirements while preserving reuse.
• Operate on a Kanban delivery model — work flows continuously, prioritised by Product Management against firm-wide value, with no individual desk independently commissioning its own tools.
• Maintain strict data stewardship, model risk and compliance standards as AI agent and decision-support solutions scale across the broking lifecycle.
• Provide ongoing support for deployed AI solutions, ensuring smooth operation and rapid resolution of issues affecting the desk.
• Translate stakeholder requirements into technical solutions, ensuring alignment with both business objectives and the firm's enterprise technical standards.
• Present project updates and key developments to broking leadership, Technology and governance stakeholders — demonstrating value, adoption and progression through the team's tiered scope (productivity, advisory, decision-making).

Experience / Competences

• Strong production engineering background — track record of architecting, building and operating scalable, robust services in production environments, not just prototypes.
• Hands-on experience working with Large Language Models (LLMs), Generative AI and modern AI/ML frameworks; current on the AI tooling landscape and able to keep up as it evolves.
• Expertise in Python in AI/ML frameworks and libraries.
• Demonstrated ability to understand and engage with a complex business domain — capable of sitting with non-technical professionals, learning how they work, and translating that understanding into production tools.
• Prior exposure to financial markets, broking, trading or other front-office environments is a strong plus.
• Experience managing technical priorities on a Kanban or Agile backlog, resolving dependencies, and aligning delivery with both business value and centrally-set technical standards.
• Evidence of presenting complex technical concepts to internal professionals and business stakeholders with varying technical backgrounds, tailoring style to the audience.
• Demonstrated ability to deliver within a regulated environment — comfortable working through controls covering security, compliance, model risk, change management and audit, rather than treating governance as an obstacle.
• AWS experience, including AI services such as Bedrock and the Serverless ecosystem, with the ability to work within established cloud frameworks.
• Proficiency in front-end technologies, particularly React, with evidence of building intuitive, responsive user interfaces that integrate seamlessly with AI-driven back-end services.
• Expertise in back-end development, including building and deploying scalable APIs and microservices to support AI solutions.
• Knowledge of OAuth (Okta) for implementing secure, scalable authentication and authorisation in full-stack applications, ensuring data protection and privacy across AI solutions.
• Experience contributing to or consuming a shared component / capability library across multiple teams or regions.
• Prior experience embedding directly with business users — front-office desks, trading floors, advisory teams — rather than working purely from a central engineering function.

Personal qualities

• Proactive, adaptable and detail-oriented; thrives in fast-paced environments and embraces challenges.
• Open to innovative ideas, with a strong analytical mindset and problem-solving skills.
• Excellent communication, tailoring style to suit different audiences from brokers on the desk to Technology, Risk and senior leadership, while respecting professional and company values.
• Stays organised, remains calm under pressure, and consistently seeks opportunities for improvement.
• Strong collaborator — comfortable working as part of a small, distributed team across regions, and contributing to a shared capability set rather than building in isolation.