Lead Java Platform Engineer Job at Citi (New Castle)

Job Description

We are seeking an experienced, hands-on Senior Java Developer to contribute to the development of our engineering frameworks, with a strong focus on microservice architecture. This senior engineering leadership role merges hands-on technical contribution with organizational accountability. The ideal candidate will remain deeply involved in the code and architecture while simultaneously owning the platform strategy, defining engineering standards, and guiding a scrum team in developing core functionalities within the payments lifecycle. You will be responsible for the reliability, scalability, security, and evolution of a global cheque payment platform and will play a pivotal role in integrating AI into both the platform and the engineering workflow.

Job Responsibility

Actively code in Java developing reusable frameworks while performing system design, architecture reviews, and code reviews for the core cheque payment platform
Contribute to the design of distributed, fault-tolerant, real-time systems for high-volume, low-latency transaction processing
Write, review, and refactor production-grade code in Java setting a high technical standard for the team
Independently design event-driven, microservices-based architectures utilizing REST APIs, Java and React
Apply hands-on experience with Kafka, including message schema design, topic partitioning, consumer group strategies, and fault-tolerant processing
Design and govern data architecture across Oracle (SQL) and MongoDB (NoSQL), covering schema design, indexing strategies, query optimization, and data consistency patterns
Champion continuous development, feature flags, and progressive delivery, contributing to the design and optimization of CI/CD pipelines
Produce and review Architecture Decision Records (ADRs) and technical design documents for key platform components
Maintain and enforce engineering standards within the scrum team, including Test-Driven Development (TDD), reusable framework development, CI/CD, secure coding, and observability
Conduct code reviews for critical platform components, providing detailed technical feedback to enhance team quality and capacity, ensuring the development of scalable and reusable services
Drive the adoption of AI-powered quality practices, including leveraging tools like GitHub Copilot for coding, utilizing LLMs (Gemini experience preferred) to improve payment processing quality, and implementing automated test script generation and vulnerability remediation
Lead performance engineering initiatives, including profiling JVM-based applications Java identifying performance hotspots, and optimizing critical settlement processing paths
Own the security and compliance posture of the cheque payment platform by participating in threat modeling, vulnerability assessments, and secure design reviews
Ensure all engineering delivery aligns with Citi Engineering Excellence Standards, including CI/CD, DevOps, cloud-native practices, and modern ways of working
Define and own the engineering roadmap for modernizing the cheque payment platform, migrating global components from monolithic mainframe and legacy applications to a reusable microservices architecture
Develop strong domain knowledge in the payment lifecycle, settlement, and cheque image processing to inform sound engineering decisions
Own the platform's SLA commitments, driving architectural decisions to meet availability, throughput, and latency targets
Develop cross-platform integration by governing API contracts, data flows, and system dependencies across the Payments, Settlements, DDA, and Data Lake ecosystems
Drive capacity planning and investment prioritization, making informed decisions on platform scaling, technology refresh, and resource allocation
Partner with Operations, Risk, Compliance, and Business teams to ensure the platform meets all regulatory requirements and business needs
Act as the primary engineering point of contact for the core Cheque Processing pillar, engaging with senior business, technology, and operations stakeholders
Clearly communicate platform health, delivery progress, engineering strategy, and risks to senior leadership
Partner with Product, Operations, Risk, Finance, and Compliance teams to align engineering priorities with business and regulatory needs
Demonstrate the ability to pivot direction to meet timelines and delivery commitments with tactical solutions, while maintaining a clear vision for strategic platform development

Requirements

Extensive hands-on experience in high-throughput, production-grade Java engineering, including JVM performance tuning
Hands-on experience building RESTful APIs with frameworks such as Spring MVC or Spring Boot
Proven experience designing microservices ecosystems, including service decomposition, API design, inter-service communication, and cloud engineering
Deep, hands-on expertise in Kafka, including topic design, partitioning, consumer groups, exactly-once semantics, and high-throughput stream processing
Hands-on experience with profiling and optimization, including JVM tuning, garbage collection (GC) optimization, thread management, and memory profiling
Practical experience designing resilience patterns such as circuit breakers, bulkheads, failover, and disaster recovery
Hands-on expertise in Oracle (SQL) and Microsoft SQL for schema design, query optimization, and indexing, as well as MongoDB (NoSQL) for document modeling, aggregation pipelines, sharding, and replica sets
Hands-on experience with OpenShift/AWS, Kubernetes, and Docker for container orchestration, autoscaling, and cloud-native deployment
Experience designing and owning CI/CD pipelines aligned with enterprise-level Engineering Excellence Standards. Experience with tools like Jenkins and Gradle/Maven
Hands-on experience with distributed tracing, intelligent alerting, and AI-driven observability using tools like Grafana
Practical experience with threat modeling, vulnerability assessments, and secure design reviews
Experience with Agile/SAFe delivery at the program level, including PI planning, cross-team dependency management, and delivery governance

Nice to have

Hands-on experience with real-time ML model serving, including feature stores, online inference, and model monitoring
Familiarity with Retrieval-Augmented Generation (RAG) patterns, vector databases (e.g., Pinecone, Weaviate), or agentic AI frameworks (e.g., LangChain, AutoGen)
Knowledge of MLOps practices such as model versioning, deployment pipelines, and production model monitoring
Experience with chaos engineering and resilience testing, including fault injection and production readiness reviews
Knowledge of reconciliation and exception handling patterns in settlement workflows
Familiarity with prompt engineering and LLM fine-tuning in a regulated enterprise context
Hands-on expertise in Python for data pipelines, AI/ML integration, scripting, and automation
Experience with large-scale transformation projects, including migrating mainframe components (COBOL, Assembler) and legacy systems (C++, .NET) to a microservices architecture
Experience with technology investment governance and engineering budget management

What we offer

Discretionary and formulaic incentive and retention awards
Medical, dental & vision coverage
401(k)
Life, accident, and disability insurance
Wellness programs
Paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays

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