Lead Software Engineer (XVA) – VP

Overview

In this Lead Software Engineer role, you will design and deliver scalable, production-grade software for XVA risk at a global bank. You will integrate AI and ML into core risk workflows, driving technical agendas across cross-functional teams. You’ll own projects end-to-end, balance business needs with regulatory requirements, and mentor engineers to raise capability in modern engineering and AI tooling. This is a hands-on, high-impact opportunity to shape risk analytics at scale and work with senior partners to redefine XVA risk management.

Pay / Benefits

• 27 days annual leave (plus bank holidays)
• discretionary annual bonus
• private medical care & life insurance
• Employee Assistance Program
• pension plan
• paid parental leave

Responsibilities

• Design, build, and maintain scalable XVA risk software meeting enterprise standards
• Embed AI/ML into core XVA workflows to automate processes and improve analytics
• Own projects end-to-end from design to production release, coordinating with engineering, business, and ops
• Lead technology projects, manage timelines and dependencies, keep team unblocked
• Translate business requirements into clear specifications and working software
• Drive Agile delivery across cross-functional, distributed teams
• Ensure solutions meet regulatory/compliance requirements and proactively manage risks
• Mentor engineers and analysts, raise quality and modern engineering practices

Key requirements

• Extensive hands-on software engineering at VP level or equivalent
• Strong Python or Java, production-grade systems in financial services
• Hands-on AI/ML in production environments with Generative AI tooling potential
• Ability to independently drive a technical agenda and architectural decisions
• Knowledge of distributed systems, microservices, and scalable data processing
• Domain knowledge in XVA, market risk, or related regulatory frameworks such as FRTB or Netted CVA
• Clear communication to technical and non-technical stakeholders
• Bachelor’s degree in Computer Science, Engineering, or related discipline

• Excellent communication skills with non-technical audiences
• Strategic thinking and ability to drive a technical agenda
• Mentorship and team leadership by example
• Python or Java proficiency
• Production AI/ML in financial services
• Generative AI tooling for engineering workflows

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