Description
We are seeking a Quantitative AI Platform Engineering Director to provide quantitative and analytical expertise to support trading strategies, risk management, and decision-making within the investment banking domain.
The successful candidate will design and develop shared AI platform capabilities used across Global Markets, build scalable infrastructure for machine learning and generative AI workloads, and define architectures for model deployment, inference, orchestration, and monitoring.
Key responsibilities include:
AI Engineering & Platform Development
- Design and develop shared AI platform capabilities used across Global Markets.
- Build scalable infrastructure for machine learning and generative AI workloads.
- Define architectures for model deployment, inference, orchestration, and monitoring.
- Develop reusable frameworks, APIs, and services that accelerate AI delivery across multiple teams.
- Evaluate emerging technologies and establish best practices for the adoption of AI at scale.
MLOps & LLMOps
- Design and implement MLOps and LLMOps frameworks supporting the full model lifecycle.
- Establish standards for model deployment, versioning, evaluation, monitoring, and observability.
- Improve reproducibility, governance, and operational resilience of AI systems.
- Define processes and tooling for prompt management, agent evaluation, and model performance tracking.
- Build automation that improves the speed and quality of AI development and deployment.
Cloud & Infrastructure
- Design cloud-native architectures supporting AI applications and services.
- Optimise utilisation of GPU infrastructure and specialised compute resources.
- Partner with Technology teams on containerisation, orchestration, and deployment strategies.
- Improve scalability, reliability, and cost efficiency of AI workloads.
- Contribute to the evolution of the firm's AI platform and infrastructure strategy.
Director Expectations
- Manage a business function, providing significant input to function-wide strategic initiatives.
- Lead a large team or sub-function, leading other people managers and embedding a performance culture aligned to the values of the business.
- Provide expert advice to senior functional management and committees to influence decisions made outside of own function.
- Manage, coordinate, and enable resourcing, budgeting, and policy creation for a significant sub-function.
Requirements
- Proven track record delivering large-scale engineering or AI platform initiatives.
- Expert Python development skills.
- Strong software engineering and architecture experience.
- Experience building production machine learning or generative AI systems.
- Excellent understanding of distributed systems, APIs, and modern software architectures.
- Experience working with cloud-native environments and container platforms.
- Experience with CI/CD, automated testing, observability, and production support.