Java Engineering Lead, Vice President

Citigroup Global Markets Limited
London
6 months ago
Applications closed

Related Jobs

View all jobs

Data Engineering Lead

Data Engineering Lead

▷ 3 Days Left! Head of Data Engineering...

Head of Software Engineering | £150k – Java, Machine Learning, and Data-Driven Innovation

Software Engineering Manager | £110k – Java, Vue.js & AWS

Lead Data Engineer

Come, work with us!

Citi, the world leading global bank, has approximately 200 million customer accounts and a presence in more than 160 countries and jurisdictions worldwide. Citi provides consumers, corporations, governments, and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management. Citi enables clients to achieve their strategic financial objectives by providing them with cutting-edge ideas, best-in-class products and solutions, and unparalleled access to capital and liquidity.

The Stress testing Team is responsible for delivering Stress testing related solutions to Citi's risk & finance organization which manages Citi's exposure to financial institutions, governments and corporates that trade with Citi. The team engineers, builds and maintains software used to compute metrics that help mitigate Citi's exposure to counterparty default & help meet regulations like CECL. GSST, IFRS9, CCAR.

Who you are:

  • You've got a positive energy. You are optimistic about the future and determined to get there.
  • You appreciate open and direct communication. You are both - an active communicator and an eager listener.
  • You can switch context & pivot on the fly. This group is a horizontal organization, and regulations are constantly changing. What you worked on yesterday may not be what you work on today.
  • You want to be part of a winning team. We build & grow with one another and you're a person who doesn't shy away from being pushed out of your comfort zone.
  • You are often cited as inspiration for the engineers and even senior engineers feel that they can learn something from you.
  • You have a "can do" attitude. We engineer & create high-quality software. Owning a problem doesn't scare you but rather empowers you to take 100% ownership.



What will you do?

  • Lead team(s) of passionate engineers supporting multiple systems who take pride in customer satisfaction and ownership
  • Set up and maintain processes that empower to move the team quickly
  • Be hands-on in technical architecture and reviews, are a strong believer in servant leadership and don't shy away from rolling up the sleeves.
  • Independently own and drive multiple critical work streams, this includes vision/direction setting, overseeing the overall planning and execution toward clear objectives with measurable key results.
  • Establish and drive adoption of design and coding best practices within your team
  • Liaise with senior stakeholders across the Risk, Finance and Front Office business organizations, and external Market Regulators to assemble execute projects across Capital spectrum.
  • Mentor and guide professional development of analysts & engineers on your team, and continuously improve software engineering practices
  • Strong written and oral presentation skills and presence
  • Collaborate with and across team to design, build and deliver high quality software meeting and exceeding client needs



Basic Requirements

  • You are a hands-on engineering manager with extensive industry experience of engineering management.
  • Experience managing individual contributors across all levels
  • Experience of managing managers (engineering or product)
  • BS or MS in Computer Science or related technical field or related experience
  • Graduate in STEM (Science, Technology, Engineering and Mathematics) or Finance disciplines.
  • Broad experience in relational and document databases, data structures, caching and reporting
  • Develop enterprise-grade applications using Java 8/JEE (and higher), No SQL, Spring, among other tools
  • A track record of managing and mentoring junior and senior engineers, preferably located across multiple time zones
  • Experience attracting and hiring top talents, including engineering leaders and software engineers
  • Proficient at working with large and complex code bases
  • Ability to be metrics / data driven and have a bias for action and result delivery



Preferred Qualifications

  • Experience in financial industry specifically in Credit Risk & Market Risk Capital domains.
  • Technologies and tools: Java, Web / Restful service development, Angular, JSON, Python, SQL, Build tools
  • Develop enterprise-grade applications using Java 8/JEE (and higher), No SQL, Spring, among other tools
  • Experience in event-driven design of Microservices and 12-factor app development standards
  • Experience building modern enterprise applications and deploying to public or private clouds including AWS
  • Experience in distributed cache systems like Apache Ignite or Redis
  • Experience in big data platforms and technologies such as Hadoop, Hive, HDFS, Presto/Starburst, Spark, and Kafka
  • Experience in Spring Framework and Cloud Computing for both batch and real-time high volume data processing
  • Experience in understanding complex SQLs and exposure to Database Design Concepts including Data Modeling, Logical/Conceptual Design



Job Family Group:
Technology

Job Family:
Applications Development

Time Type:
Full time

Citi is an equal opportunity and affirmative action employer.

Qualified applicants will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Citigroup Inc. and its subsidiaries ("Citi") invite all qualified interested applicants to apply for career opportunities. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity reviewAccessibility at Citi.

View the "EEO is the Law" poster. View theEEO is the Law Supplement.

View theEEO Policy Statement.

View thePay Transparency Posting

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.