We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Risk Quantitative Development model implementation team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for develops and manages features and enhancements to services that execute machine learning pipelines for fraud detection and risk assessment.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Architect and implement resilient, highly scalable, fault-tolerant services
• Develops secure high-quality production code, and reviews and debugs code written by others
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, equity, inclusion, and respect

• Formal training or certification on software engineering concepts and 5+ years in large-scale distributed technology projects in Java/J2EE and Linux environment.
• Experience with Service Oriented Architecture (SOA) and Expert in REST APIs.
• Hands - on experience with Core Java 5+, Spring framework (Boot , Integration, DI,Security, WS etc)
• Proficient in working with Kafka, MQ or other messaging platforms.
• Experience with any log analytic tools like ELK, Splunk etc
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Solid understanding of consumer financial products, data systems and data environments, and processes that are necessary for the implementation of Risk and Finance models

• Experience with NoSQL databases like Cassandra preferred
• Knowledge of deploying to Kubernetes is a plus
• Excellent organizational and planning skills
• In-depth knowledge of the financial services industry and their IT systems