We are seeking a Senior Engineer to fill the role of ‘Applications Development Technology Lead Analyst’ on the XiNG large scale distributed calculation platform (XiP).  

In this role you will design, build, and maintain the calculation engine at the heart of the XiP platform. This engine is responsible for c. 0.5 billion risk & suitability calculations at Citi every day. A single customer run compresses 17 million minutes of compute into a single 90-minute execution. 

Run on hundreds of thousands of pods across the entire XiP platform every day this calculation engine is both highly performant and rapidly changing to support new scenarios, technologies, and infrastructure. 

As an engineer working on the calculation engine. You will work closely with software engineers, DevOps, and our customers to ensure reliable, secure, and scalable operations of our platform. 

Responsibilities: 

Take part of the shared responsibility for the long-term strategic direction of the XiP Calculation Engine: 

Apply your experience and skills to develop the future versions of the calculation engine. This means making it faster, utilizing resources better, and scale to even greater sizes. This means adding new features without impacting performance of the platform in undesirable manner, small changes multiplied by millions of calculations have a high cost. This means solving hard problems like transferring small amounts of data to a huge number of machines. 

Serve as advisor or coach to team members, allocating and overseeing work: 

Mentor and guide mid-level developers, providing technical advice, code reviews, and career development support. Allocate tasks based on skill sets and project priorities, ensuring balanced workloads and timely delivery. Foster a collaborative and growth-oriented team environment, encouraging best practices and continuous learning. 

Implement changes and improvements to Citi's Risk Calculation Engine, including analyzing and designing improvements to the distribution mechanisms of the engine which regularly parallelizes 250,000 hours of compute into a single 90-minute execution: 

Lead the design, development, and implementation of enhancements to the Risk Calculation Engine, focusing on optimizing its distribution mechanisms. Analyze current parallelization strategies and identify opportunities to further improve efficiency, scalability, and throughput. 

Operationally support the optimization of Risk calculations by examining and providing SME level insight into the distributed execution of extremely large calculations: 

Monitor and analyze the distributed execution of large-scale risk calculations, identifying performance bottlenecks and inefficiencies. Provide subject matter expertise to guide operational improvements, leveraging deep technical knowledge to recommend and implement optimizations that enhance calculation speed and resource utilization. 

Plan, coordinate, and execute strategic changes to the engine to reach the next scaling milestone: 

Develop and manage strategic initiatives aimed at scaling the Risk Calculation Engine to meet future business demands. Coordinate with stakeholders to ensure that all scaling efforts are aligned with customer needs. 

Provide specialized customer support to optimize and improve large, distributed calculations. 

Act as a primary point of contact for clients to address issues and optimize inefficiencies that arise during distributed workload execution. 

Qualifications: 

• Multiple years professional software development experience with Java. 

• Solid experience with Java frameworks (e.g., Spring, Spring Boot, Quarkus). 

• Experience designing, building, and maintaining large-scale, distributed systems. 

• Experience with RESTful API design and implementation. 

• Strong understanding of object-oriented programming and design patterns. 

• Exposure to NoSQL databases (e.g., MongoDB, Cassandra) is a plus. 

• Exposure to cloud platforms (e.g., AWS, Azure, GCP) and containerization (e.g., Docker, Kubernetes) is desirable. 

• Experience with unit testing, integration testing, and test automation frameworks (e.g., JUnit, Mockito). 

• Experience working in Agile/Scrum development environments. 

• Practical experience with Python for scripting, automation, or data processing tasks. 

• Experience with CI/CD pipelines and DevOps practices is a plus. 

Education: 

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.