AI Data Engineer - Python, Front Office Tier 1 Investment Bank Front Office Trading Technology | Pre-Trade AI & Data
A Tier 1 Investment Bank is hiring a Vice President-level AI Data Engineer to join a strategically important pre-trade AI and data function within its global trading technology organisation.
This role sits at the intersection of AI, trading data, and front-office technology enablement. The team is focused on how modern AI capabilities, including LLMs, GPUs, and agentic workflows, can be applied across trading environments to improve business outcomes, increase efficiency, and create commercial differentiation.
This is not a narrowly defined engineering role tied to a single platform or technology stack. The bank is seeking a senior, hands-on AI/data professional who can operate across both technical and business domains, helping shape how AI is adopted within complex trading environments.
Key Responsibilities
- Work across front-office trading technology initiatives involving AI and data
- Analyse, engineer, and optimise large-scale trading datasets for AI-driven use cases
- Design and build scalable data engineering solutions to support AI and analytics workflows
- Develop approaches for exposing trading data to AI systems and workflows
- Help define and implement agentic workflows and AI-enabled operational models
- Build and support data pipelines, ingestion frameworks, and data processing workflows
- Work closely with front-office stakeholders to identify commercially valuable AI opportunities
- Provide technical and strategic input into AI adoption across trading environments
- Contribute to the development of scalable AI/data platforms aligned to business objectives
- Operate in both an advisory and hands-on engineering capacity across multiple initiatives
- Evaluate emerging AI technologies and their applicability within financial markets environments
- Collaborate with engineering, trading, data, and business teams across the organisation
Required Experience
- Strong hands-on experience working within AI, data engineering, or machine learning environments
- Advanced Python engineering and development experience within enterprise environments
- Strong experience building scalable data pipelines and distributed data processing solutions
- Proven experience working with structured and unstructured datasets at scale
- Experience designing and implementing data engineering frameworks supporting AI or analytics use cases
- Proven experience delivering practical AI outcomes rather than purely academic or research-led work
- Background within investment banking, capital markets, or another highly complex regulated environment
- Strong understanding of front-office trading technology and trading workflows
- Experience operating effectively across both technical and business-facing discussions
- Strong understanding of enterprise-scale technology environments
- Experience navigating major technology transitions or transformation programmes
Preferred Experience
- Exposure to LLMs, GPUs, and modern AI tooling/frameworks
- Experience designing or supporting AI-enabled workflows or automation
- Experience with cloud-native or distributed compute/data environments
- Understanding of pre-trade technology environments
- Experience operating across multiple asset classes
- Ability to work in technology-agnostic environments without reliance on a single stack
Technical Environment
Experience with some of the following would be beneficial:
- Python
- AI/ML frameworks and tooling
- Distributed data processing technologies
- Data pipeline and orchestration tooling
- SQL and large-scale data platforms
- API and data integration architectures
- GPU-enabled compute environments
- Cloud and hybrid infrastructure environments
Candidate Profile
The ideal candidate will combine deep technical engineering capability with commercial awareness and strong communication skills. This role requires someone capable of helping shape AI direction within a front-office trading environment, not simply executing against predefined requirements.
Candidates coming from purely academic AI backgrounds without practical implementation experience are unlikely to be suitable.
Additional Information
- High-visibility strategic hiring area
- Strong flexibility around package and level for exceptional candidates
- Opportunity to influence AI adoption within a major global trading environment