You will contribute to the design, automation, and maintenance of CI/CD pipelines and infrastructure as code to support a scalable developer platform. Additionally, you will manage monitoring, logging, and security practices to ensure high availability and efficient software delivery for the Sphere platform.
Design, build, and maintain production-grade data pipelines and infrastructure to power analytics and machine learning. Ensure the reliability, scalability, and quality of large-scale financial and time-series data flows across the organization.
The role involves bridging the gap between complex quantitative modeling and real-world financial applications by translating research signals into actionable investment strategies. The scientist will evaluate ML model outputs and design scalable quantitative models using Python and Java.
Develop and optimize a high-performance Spring Boot backend to ensure scalability, reliability, and security. Implement clean, modular Java code and collaborate with DevOps to improve CI/CD automation.
Own the strategy, roadmap, and delivery of a core product line for the Sphere platform. Lead cross-functional squads to align engineering, data science, and GTM teams toward measurable client outcomes.
Lead the design and optimization of scalable Spring Boot applications while driving architectural decisions and promoting clean code. Mentor engineers through code reviews and collaborate cross-functionally to deliver high-quality, secure backend solutions.
Develop, maintain, and optimize scalable Spring Boot applications while implementing clean, modular, and testable Java code. Collaborate with DevOps teams to improve CI/CD automation and troubleshoot backend performance and security.
You will be responsible for developing and executing comprehensive test plans while ensuring the reliability, security, and performance of AI-driven software. Additionally, you will collaborate with engineering teams to integrate testing into the CI/CD pipeline and define quality gates to maintain high standards.
