Senior Back-End Java Developer — Trading Platforms

Apps Development Senior Manager Trade Manager Zone Platform | Cash Securities Settlements | Equity Growth Initiative About the Role We are seeking a visionary and hands-on Apps Development Senior Manager to lead engineering delivery for the Trade Manager Zone (TMZ) platform within the Cash Securities Settlements group, supporting the Equity Growth Initiative . This is a core engineering leadership role at the heart of a high-impact, high-throughput financial platform that processes equity trade settlements at scale. You will lead high-performing engineering teams responsible for building, maintaining, and evolving mission-critical settlement systems — driving architectural excellence, modern delivery practices, and technical transformation. Critically, you will play a defining role in embedding Artificial Intelligence and Machine Learning into the platform — from AI-assisted development and intelligent automation to predictive analytics and GenAI-powered operational tooling — accelerating delivery, elevating code quality, and future-proofing our engineering culture. This role demands deep technical expertise, strong ownership, and the ability to lead through complexity in a regulated, fast-paced financial environment. Responsibilities: 1. Software Development & System Design Architect, design, develop, and maintain robust, scalable, and high-performance applications supporting equity trade settlement workflows on the Trade Manager Zone platform. Lead the design of distributed, fault-tolerant, real-time systems capable of handling high-volume, low-latency trade processing across global markets. Champion the use of AI-assisted coding tools (e.g., GitHub Copilot or equivalent GenAI tools) to accelerate developer productivity, reduce toil, and improve code quality. Drive adoption of trunk-based development practices to enable continuous integration and rapid, safe delivery. Ensure code is clean, maintainable, and testable — adhering to SOLID principles , design patterns, and platform engineering standards. Actively contribute to hands-on coding, code reviews, and refactoring to maintain high engineering standards across the team. Own the technical design of key platform components, producing clear architecture documentation and decision records. 2. Engineering Excellence & AI-Driven Quality Champion Test-Driven Development (TDD) , Behavior-Driven Development (BDD) , and high unit test coverage as non-negotiable engineering standards. Introduce AI-powered code review tooling to complement human reviews — catching security vulnerabilities, anti-patterns, and performance issues at scale. Apply predictive quality analytics to identify high-risk code changes before they reach production. Drive the adoption of automated testing frameworks across unit, integration, regression, and end-to-end test layers, including AI-assisted test generation. Implement and enforce secure coding practices , augmented by AI-driven vulnerability scanning, performing assessments and ensuring compliance with financial industry security and regulatory standards. Advocate for infrastructure as code , continuous monitoring, and AI-assisted observability (e.g., anomaly detection, intelligent alerting, root cause analysis) to enhance platform reliability. Embed CI/CD pipelines and DevOps practices deeply into the team's delivery workflow, aligned to Citi Engineering Excellence Standards . Drive a culture of zero-defect engineering — proactive quality ownership from design through to production. 3. Advanced AI & Data Integration Lead the integration of AI and ML capabilities into the Trade Manager Zone platform — including intelligent exception handling, anomaly detection, predictive settlement failure analysis, and automated reconciliation workflows. Leverage Large Language Models (LLMs) and GenAI APIs to embed intelligent capabilities into platform operations — such as natural language interfaces for trade operations, automated summarization of settlement exceptions, and AI-driven decision support. Partner with data engineers and ML practitioners to design and operationalize AI/ML pipelines that consume real-time trade data and deliver actionable intelligence. Apply advanced data integration patterns to ensure high-quality, low-latency data flows across platform components, supporting both operational and analytical AI use cases. Evaluate and adopt AI/ML frameworks and tooling appropriate for high-throughput financial systems, ensuring models are production-grade, explainable, and compliant with risk and governance standards. Champion responsible AI practices — ensuring fairness, auditability, and regulatory alignment in all AI-driven platform capabilities. Drive the team's AI adoption roadmap — identifying high-value opportunities to apply GenAI, ML, and intelligent automation to real platform engineering and operational challenges. 4. Platform & Domain Expertise Develop deep understanding of equity trade lifecycle, settlement mechanics, and cash securities processing to make informed technical decisions aligned with business needs. Partner with business analysts, product owners, and operations teams to translate complex settlement workflows and regulatory requirements into robust technical solutions. Ensure platform components meet SLA, SLO, and SLI targets for availability, throughput, and latency in a mission-critical environment. Collaborate with downstream and upstream system owners across the Cash Securities Settlements ecosystem to ensure seamless integration and data integrity. Drive continuous platform modernization — improving maintainability, scalability, and operational efficiency of TMZ components. 5. Technical Leadership & People Management Lead, mentor, and grow a team of engineers — setting high engineering standards and fostering a culture of craftsmanship, AI curiosity, accountability, and continuous learning . Mentor engineers on AI tool usage, prompt engineering, and responsible AI practices , building internal AI literacy across the team. Partner with architects, platform engineers, and cross-functional teams to design scalable, distributed, and AI-ready systems . Collaborate closely with DevOps, SRE, and infrastructure teams to optimize deployments, observability, and production resilience — leveraging AIOps capabilities . Lead technical discussions, architecture reviews, and design sessions — providing clear guidance on engineering decisions, AI integration patterns, and trade-offs. Drive capacity planning, technical roadmap execution , and engineering delivery commitments for the TMZ platform. Represent the engineering team in stakeholder forums, providing transparent updates on delivery progress, risks, and technical health. Skills and Qualifications Must-Have Skills 1. Programming Languages Kotlin Primary language for platform services; strong hands-on proficiency required Python Used for data pipelines, AI/ML integration, scripting, and automation Java Core backend development; deep expertise in production-grade Java applications 2. System Architecture — Real-Time, High-Throughput & Performance Optimization Microservices Architecture Design and delivery of loosely coupled, independently deployable services at scale Event-Driven & Messaging Systems Hands-on experience with Kafka or Solace for real-time, high-throughput event streaming and messaging Low-Latency & High-Performance Computing Proven experience optimizing systems for sub-millisecond to millisecond response times in high-volume financial environments High Availability & Fault Tolerance Design patterns for resilient systems — circuit breakers, bulkheads, failover, and graceful degradation Databases Strong proficiency in Oracle (SQL) for transactional data and MongoDB (NoSQL) for flexible, high-throughput data models 3. Advanced Data & AI Integration AI & ML Integration Experience integrating AI/ML models into production systems — including model serving, inference pipelines, and real-time scoring GenAI Tooling Hands-on experience with AI-assisted development tools (GitHub Copilot, or equivalent) and LLM API integration Data Engineering Strong understanding of data pipelines, streaming data processing, and data quality patterns in high-volume environments Intelligent Automation Applying ML to automate exception handling, anomaly detection, and operational workflows in financial platforms AI Governance Familiarity with responsible AI principles — explain ability, auditability, and compliance in regulated environments 4. Cloud & DevOps — Citi Engineering Excellence Standards Cloud-Native Engineering Hands-on experience with AWS, Kubernetes, and Docker for scalable, containerized deployments CI/CD Pipelines Strong proficiency in building and maintaining CI/CD pipelines aligned to Citi Engineering Excellence Standards Trunk-Based Development Feature flags, progressive delivery, and continuous integration as core delivery practices Observability & Monitoring Experience with production monitoring, distributed tracing, intelligent alerting, and SRE practices Secure Engineering AI-augmented vulnerability assessments, secure coding standards, and compliance in regulated financial environments Agile Delivery Strong experience in Agile/SAFe frameworks — backlog management, sprint delivery, and cross-team dependency management 5. Good-to-Have Skills Experience with real-time ML model serving in low-latency, high-throughput environments (e.g., feature stores, online inference). Familiarity with Retrieval-Augmented Generation (RAG) , vector databases (e.g., Pinecone, Weaviate), or AI agent frameworks (e.g., LangChain, AutoGen). Knowledge of MLOps practices — model versioning, deployment pipelines, and monitoring in production. Understanding of AIOps — AI-driven incident management, anomaly detection, and intelligent observability. Knowledge of equity trade lifecycle, settlement mechanics, or cash securities processing . Understanding of regulatory compliance frameworks relevant to securities settlement (e.g., T+1, CSDR). Experience with performance profiling and tuning of JVM-based applications (Kotlin/Java) under high load. Knowledge of risk management, reconciliation, and exception handling patterns in settlement workflows. Familiarity with prompt engineering and fine-tuning strategies for LLMs in an enterprise context. What We Are Looking For This role is for an engineer at heart who has grown into a leader — someone who: Stays close to the code — actively participates in design, review, and technical problem-solving alongside the team. Thinks AI-first — actively seeks opportunities to apply AI and GenAI to engineering and operational challenges, not just product features. Owns outcomes — takes full accountability for platform quality, reliability, and delivery commitments. Thrives in complexity — comfortable navigating the technical and operational complexity of mission-critical financial systems. Raises the bar — consistently pushes for higher engineering standards, better test coverage, cleaner architecture, and more resilient systems. Embraces AI pragmatically — identifies high-value opportunities to apply AI/ML to real platform problems, without losing sight of engineering fundamentals. Inspires curiosity — creates an environment where engineers are excited to learn, experiment, and grow with AI. Builds great teams — invests in people, creates psychological safety, and develops the next generation of engineering talent. Education: Bachelor’s degree/University degree or equivalent experience Master’s degree preferred ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Primary Location: Jersey City New Jersey United States ------------------------------------------------------ Primary Location Full Time Salary Range: $142,320.00 - $213,480.00 In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit . Available offerings may vary by jurisdiction, job level, and date of hire. ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Anticipated Posting Close Date: ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. 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 review Accessibility at Citi . 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