Top Software Engineer Jobs

Develop robust, performant pricing, trading, and risk systems using Python. Collaborate with Quant team on pricing and analytic components. Demonstrate best practices in software development lifecycle.

Lead a squad of engineers to design, implement, and maintain core areas within Chase UK. Manage delivery, collaborate with Product team, establish agile practices, and foster top engineering standards. Required qualifications include strong technical background, business-driven mentality, progressive mindset, JVM language experience, automation skills, and microservices design proficiency.

Lead the data transformation strategy and manage complex data projects within Investment Banking businesses. Drive data quality and automation, mentor and develop a team of data analysts and professionals, and maintain strong stakeholder relationships. Strong technical expertise in SQL, data modeling, and data processing tools like Alteryx and Tableau required.

Lead Software Engineer at JPMorgan Chase responsible for delivering cutting-edge solutions using cloud-native microservice architecture applications. Requires proficiency in Java and hands-on experience in back-end development. Strong collaborative and customer-facing skills are essential.

Responsible for defining and articulating the Chief Data Office vision and strategy, executing strategic initiatives, and leading critical projects to enable AI-ready data and manage data risk effectively.

Apply sophisticated machine learning methods to banking applications including risk assessment, trading models, customer relationship management, and pricing models. Collaborate with various lines of business within JP Morgan to develop scalable tools leveraging machine learning and deep learning models for real-world problems in finance, economics, and operations. Lead projects in developing production-level machine learning applications.

Lead the execution of AI solutions in Securities Services Operations, construct robust and scalable AI functionalities, work with software engineering teams, collaborate with business domain experts, refine machine learning models, stay updated with AI trends, offer technical mentorship, and disseminate best practices.