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FX Risk — Lead Java Developer | Vice President

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Citi
Full Time position
Listed on 2026-05-31
Job specializations:
  • Software Development
    AI Engineer, Software Engineer, Cloud Engineer - Software, DevOps
Salary/Wage Range or Industry Benchmark: 100000 - 125000 GBP Yearly GBP 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

Overview

Citi’s Markets technology team is growing at lightning speed, and we’re looking for talented technologists to help build the future of global banking. Our teams are creating innovations used across the globe. As the world’s most global bank, Citi provides an opportunity to touch every corner of the globe and deal with incomparable trade volumes, scale and impact. We’re looking for new, innovative ways to push the boundaries of financial technology.

Citi’s global technology team spans 84 countries, with almost 30,000 colleagues managing thousands of projects across the globe. Our team is young but rapidly growing. Join an environment with a laser focus on growth and progress and take your career to the next level through the power of Citi’s unmatched globality and vast expertise.

As a Lead Java Developer – Vice President within Citi’s FX Risk technology team, you’ll be at the intersection of high‑stakes financial engineering and the next generation of AI‑powered software development. You’ll architect and deliver the systems that power real‑time FX risk management for one of the world’s largest financial institutions, working in an environment where AI is not a future ambition – it’s how we work today.

What

You’ll Do
  • Lead end‑to‑end delivery of complex, high‑performance Java applications supporting FX risk management across global markets
  • Architect scalable, low‑latency solutions that process real‑time risk data at scale – designing for resilience, performance, and security from day one
  • Drive technical direction and key decisions – from system design and architectural choices to setting engineering standards across the team
  • Translate complex business requirements into robust, high‑quality code – working closely with quantitative analysts, traders, and business stakeholders
  • Craft high‑quality, scalable software in an agile environment, leveraging AI‑powered coding tools to accelerate delivery without compromising standards
  • Share expertise and raise the bar – act as a technical reference point for the team, influencing engineering quality through example, guidance, and knowledge sharing
  • Champion innovation – actively evaluate, propose, and adopt new technologies and frameworks; this team has the mandate and appetite to bring in better tools
  • Own quality – participate in mandatory cross‑team code reviews and peer engineers, ensuring adherence to security, quality, and compliance standards
  • Operate in production – take ownership of L3 production support issues, provide timely resolutions, and deliver long‑term remediation fixes that address root causes – not just symptoms
  • Support testing cycles and post‑production deployment – from writing TDD‑first code to validating releases in a weekly cadence
  • Contribute to Citi’s technology strategy, influencing how the firm approaches risk technology at a global scale
Your AI‑Powered Toolkit Coding & Code Generation
  • Git Hub Copilot – multi‑model AI coding assistant (GPT, Claude, Gemini) integrated directly into your IDE for code completion, generation, and explanation
  • Devin.

    AI – agentic code generation for complex, multi‑step development tasks
  • Prompt Engineering & GenAI Optimisation – techniques actively used to get the best out of every model in the stack
Code Review & Quality
  • Citi Squad – Citi’s internal automated code review platform, catching issues before they reach production
  • AI‑assisted cross‑team peer reviews – mandatory, structured, and supported by tooling that flags security risks, missing tests, and policy violations
LLMs & Stylus Work spaces
  • Large Language Models:
    Gemini, OpenAI, Claude, Llama, and local models
  • Stylus Work spaces – Citi’s in‑house GenAI platform (powered by Gemini), connected to internal systems including Jira, Git Hub, Slack, and Teams – enabling agentic AI workflows across the SDLC
Deployment & Dev Ops
  • Enterprise Dev Ops Pipeline – CI/CD with JIRA, Zephyr, Git Hub, Harness, Artifactory
  • Container orchestration:
    Docker, Kubernetes, Open Shift
  • Monitoring tooling – production observability built in from day one
The Platform You’ll Be Building On

This role is centred around a greenfield application – built from scratch, now three years in production, and…

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