Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Owns the technology agenda for the EMEA region, setting direction and ensuring timely, high-quality delivery in partnership with front office traders and quantitative research and trading
Drives cross-functional initiatives across Risk Technology, Market Data Technology, and related platforms to deliver integrated solutions across the trade lifecycle
Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Builds strong, trusted relationships with front office and quantitative research and trading stakeholders, translating market and analytical needs into technical solutions
Contributes to a team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
Hands-on practical experience delivering system design, application development, testing, and operational stability
Strong knowledge of Python
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
In-depth knowledge of the financial services industry and their IT systems
Practical cloud native experience
Experience working closely with front office and/or quantitative research and trading in a markets environment
Genuine interest in nonlinear rates markets and the businesses they support
Preferred qualifications, capabilities, and skills
Experience building or supporting pricing, marking, market data, or risk platforms for a trading business
Strong cross-functional leadership skills, with a track record of driving outcomes across multiple technology and business teams
Experience operating across global teams and regions, with strong communication skills to influence both technical and trading stakeholders
