Leads software engineering efforts within Finance Technology, designing, developing, testing, and troubleshooting secure, scalable applications. Builds production code with Java, React, Spring Boot, AWS, and Terraform; improves operational stability through automation. Leads vendor and architecture evaluations, promotes engineering practices, and drives multi-team adoption of AI-assisted development and SDLC automation with appropriate governance, security, resiliency, and responsible AI controls.
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer at JPMorgan Chase within the Finance Technology team, you are an integral part of an agile group that delivers trusted, market-leading technology products in a secure, stable, and scalable way. You drive significant business impact through your capabilities and contributions, applying deep technical expertise and problem-solving skills to tackle diverse challenges across multiple technologies and applications. You will help foster a collaborative team culture and support the advancement of technology within the Corporate Technology division.
Job responsibilities
As a Senior Lead Software Engineer at JPMorgan Chase within the Finance Technology team, you are an integral part of an agile group that delivers trusted, market-leading technology products in a secure, stable, and scalable way. You drive significant business impact through your capabilities and contributions, applying deep technical expertise and problem-solving skills to tackle diverse challenges across multiple technologies and applications. You will help foster a collaborative team culture and support the advancement of technology within the Corporate Technology division.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting, thinking beyond routine approaches to build solutions or break down technical problems
- Develops secure, high-quality production code, and review and debug code written by others
Identify opportunities to eliminate or automate remediation of recurring issues to improve operational stability of software applications and systems - Leads evaluation sessions with external vendors, startups, and internal teams to probe 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
- Sets and scale operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establish measurable expectations and ensure consistent validation, security, resiliency, and reuse of proven patterns
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets
Required qualifications, capabilities, and skills
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in Java, React JS, and Spring Boot Framework
- Experience in AWS ECS, EKS, and Terraform
- Demonstrated proficiency in development using agentic development tools, Copilot, and Claude Code
- Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning)
- 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
- Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working, measuring outcomes, and ensuring secure handling of sensitive inputs/outputs
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations; ability to coach managers/leads and influence leaders on safe scaling patterns
Preferred qualifications, capabilities, and skills
- Familiarity with Databricks
- Exposure to cloud technologies
- Experience with Typescript
- Knowledge on API / Microservices
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