Lead AI Engineer in London

The TP ICAP Group is a world leading provider of market infrastructure. Our purpose is to provide clients with access to global financial and commodities markets, improving price discovery, liquidity, and distribution of data, through responsible and innovative solutions. Through our people and technology, we connect clients to superior liquidity and data solutions.

This is a newly created opportunity within the Global Broking business for a senior AI Engineer who wants to work directly with front-office users, solve real commercial problems, and help build the firm's AI capability from the ground up. Joining the AI Solutions Group in its formative stage, you will operate at the intersection of brokers, product management and technology. Rather than working from a central technology function, you will spend the majority of your time directly alongside front-office teams, understanding how they generate revenue, manage risk and serve clients, then translating those challenges into production-grade AI solutions that deliver measurable business value.

This is a hands-on engineering role for someone who enjoys building as much as shaping. While TP ICAP already has established AI governance, delivery frameworks and technology foundations, you will play a contributing role in evolving those capabilities, contributing patterns, frameworks and reusable components that will become part of the firm's long-term AI operating model. The team is intentionally small and entrepreneurial. The successful candidate will help define how embedded AI engineering operates within Global Broking, working across multiple asset classes and regions. As the function grows, there will be opportunities to influence technical direction, mentor additional engineers and help establish a scalable delivery model that supports front-office teams globally.

Success in this role is measured by outcomes rather than experiments. We are looking for an engineer who can identify opportunities, engage directly with users, rapidly turn ideas into production solutions and demonstrate clear adoption and business impact.

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

Essential

• 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 experience partnering directly with front-office, revenue-generating or client-facing users, identifying opportunities to improve workflows and delivering technology solutions that create measurable business value.
• Able to build credibility with senior stakeholders and translate business problems into production-grade AI products.
• 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.

Desired

• 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.

Location: London