Lead Java Developer - Senior Vice President

Citi is hiring a Senior Java Engineer to lead the technical transformation of its global cheque payment platform — a critical infrastructure at the heart of high-volume financial transaction processing. In this senior engineering role within the Payments Platform organisation, you will combine deep hands‑on coding in Java with platform strategy ownership, guiding a scrum team through the modernisation of core payment systems from legacy mainframe architectures to cloud-native microservices.

This is a rare opportunity to architect and deliver at scale while embedding AI-driven practices into both the platform and the engineering workflow.

• Design and build production-grade Java microservices for a high-volume, low-latency cheque payment platform, authoring reusable frameworks, conducting architecture reviews, and setting the technical standard for the team.

• Architect event-driven, fault-tolerant distributed systems using Apache Kafka — covering message schema design, topic partitioning, consumer group strategies, and exactly-once processing semantics.

• Define and execute the engineering roadmap for modernising the cheque payment platform, migrating global components from monolithic mainframe applications to scalable, cloud-native microservices.

• Own the platform's data architecture across Oracle, Microsoft SQL, and MongoDB — governing schema design, query optimisation, indexing strategies, and data consistency patterns across relational and No
  
  SQL stores.

• Drive AI-powered engineering quality across the team — integrating tools such as Git Hub Copilot and LLMs (including Gemini) for automated test generation, vulnerability scanning, and enhanced payment processing accuracy.

• Lead performance engineering for JVM-based applications — profiling hotspots, tuning garbage collection, optimising thread management, and improving critical settlement processing paths.

• Own the security and compliance posture of the platform through threat modelling, vulnerability assessments, and secure design reviews, ensuring alignment to engineering excellence standards across CI/CD, Dev Ops, and cloud-native delivery.

• Act as the primary engineering point of contact for the cheque processing pillar, communicating platform health, delivery progress, and engineering strategy to senior business and technology stakeholders.

• Extensive hands‑on Java engineering experience in high-throughput, production‑grade environments, including JVM performance tuning, GC optimisation, and thread and memory profiling.

• Proven ability to design and deliver microservices‑based architectures using Spring Boot or Spring MVC, with hands‑on expertise in RESTful API design, service decomposition, and inter‑service communication patterns.

• Deep practical knowledge of Apache Kafka, including topic design, partitioning strategies, consumer groups, exactly‑once semantics, and high-throughput stream processing.

• Hands‑on expertise with Oracle SQL and MongoDB, covering schema design, query optimisation, indexing, aggregation pipelines, sharding, and replica set configuration.

• Cloud‑native engineering experience with Open Shift, AWS, Kubernetes, and Docker — including container orchestration, autoscaling, and cloud-native deployment practices.

• Hands‑on ownership of CI/CD pipelines using tools such as Jenkins, Gradle, and Maven, with experience in Dev Ops practices, observability tooling such as Grafana, and distributed tracing.

• Demonstrated experience delivering at scale within Agile or SAFe frameworks, including PI planning, cross‑team dependency management, and programme‑level governance.

• Familiarity with real‑time ML model serving, MLOps practices, RAG patterns, or agentic AI frameworks such as Lang Chain or Auto Gen in an enterprise or regulated environment.

• Experience leading large‑scale legacy modernisation programmes — migrating mainframe components written in COBOL, Assembler, or C++ into cloud‑native microservices.

• Hands‑on Python skills applied to data pipeline engineering, AI and ML integration, and workflow automation.

• Knowledge of reconciliation and exception handling patterns…