At a Glance
- Tasks: Lead innovative software projects and integrate AI solutions in a dynamic financial environment.
- Company: Join Citi's cutting-edge XVA Technology team in London.
- Benefits: Enjoy 27 days annual leave, competitive salary, and professional development opportunities.
- Other info: Collaborate with top engineers and engage in exciting, high-impact projects.
- Why this job: Make a global impact with your code and ideas in a high-stakes role.
- Qualifications: Strong software engineering background with expertise in Python or Java and AI solutions.
The predicted salary is between 80000 - 100000 £ per year.
Join Citi's XVA Technology team in London as a Lead Software Engineer at Vice President level, and take on a role at the intersection of advanced software engineering and AI‑driven innovation — at a firm where your code, your decisions, and your ideas operate at global scale. This role is built for a hands‑on engineer with deep AI and software development expertise who can independently set and drive a technical agenda — building production systems, embedding intelligent tooling, and owning project outcomes across a complex, high‑impact domain. You will work alongside high‑calibre engineers and engaged business partners to architect, build, and deliver solutions that redefine how XVA risk is calculated and managed globally.
Responsibilities
- Design, build, and maintain scalable, high‑performance software solutions for XVA risk systems, writing and reviewing production‑quality code while ensuring alignment with enterprise architecture standards.
- Build and integrate AI and Machine Learning solutions into core XVA workflows — applying Generative AI tooling to automate processes, improve analytical accuracy, and measurably accelerate engineering output.
- Take end‑to‑end ownership of technology projects — from initial design and development through to production release — coordinating across engineering, business, and operations teams to keep projects on track.
- Lead and run technology projects with confidence, managing timelines, dependencies, and stakeholder expectations while keeping the engineering team focused and unblocked.
- Translate complex business requirements from Risk, Operations, and Technology partners into clear functional specifications, well‑structured solution designs, and working software.
- Drive Agile delivery practices across cross‑functional and distributed teams, facilitating sprint planning, stand‑ups, retrospectives, and release coordination.
- Define project scope and ensure all solutions meet regulatory and compliance requirements, proactively identifying and resolving technical and delivery risks across market risk technology projects.
- Mentor engineers and analysts, sharing technical knowledge, setting quality standards, and building team capability — particularly in modern engineering practices and AI tooling.
Required Qualifications & Skills
- Extensive hands‑on software engineering experience at Vice President level or equivalent, with a strong foundation in Python or Java and a track record of delivering production‑grade systems in a financial services environment.
- Hands‑on experience building and deploying AI or Machine Learning solutions in a production environment, with the ability to identify where Generative AI tooling can be embedded to measurably improve engineering workflows and analytical capabilities.
- Ability to independently own and drive a technical agenda — setting direction, making architectural decisions, and managing project outcomes without requiring close oversight.
- Solid understanding of distributed systems, microservices architecture, and scalable data processing, with the ability to make and defend architectural decisions under real‑world constraints.
- Domain knowledge in XVA (X‑Value Adjustment), market risk, or related regulatory frameworks such as FRTB or Netted CVA, with the ability to engage credibly with both technical and business stakeholders.
- Clear, confident communication skills — able to present complex technical concepts to non‑technical audiences and align diverse stakeholders around a shared project plan.
- Bachelor’s degree in Computer Science, Engineering, or a related discipline.
Beneficial Skills & Qualifications
- Experience leading AI or automation initiatives within a financial services engineering team, including tooling evaluation, integration, and measuring productivity outcomes.
- Familiarity with cloud platforms (AWS, Azure, or GCP) and DevOps practices including containerisation, CI/CD pipelines, and infrastructure as code.
- Master’s degree in Computer Science, Finance, or a related field; professional certifications such as PMP, CSM, or AI/ML credentials are a plus.
- Prior experience applying AI or automation specifically within risk analytics, trading systems, or regulatory reporting workflows.
This job description provides a high‑level review of the types of work performed. Other job‑related duties may be assigned as required.
Benefits
27 days annual leave (plus
