Lead Software Engineer

Lead/Manager Software Engineer

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 JPMorganChase within the Asset and Wealth Management, 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 conducting critical technology solutions across multiple technical areas within various PBATax functions in support of the firm’s business objectives.

Job responsibilities

• Designs, develops, and troubleshoots creative software solutions, applying innovative approaches to solve complex technical problems.
• Writes secure, high-quality production code; reviews and debugs code from other developers.
• Identifies and automates remediation of recurring issues to enhance operational stability of applications and systems.
• Manages team workflow, drive improvements in SDLC, testing, and coding standards.
• Develops scalable, real-time processing solutions using agile methodologies.
• Collaborates with stakeholders to gather requirements and deliver effective solutions.
• Works with application support teams to maintain and support the platform.
• Adds to team culture of diversity, opportunity, inclusion, and respect
  

Required qualifications, capabilities, and skills

• Formal training or certification in software engineering concepts and 5+ years of applied experience.
• Experience in Python, Java, SQL, Spring, Springboot, Rule Engines ( BPMN and DMN), Hibernate, Database and AWS Terraform.
• Experience in working on cloud platforms like public cloud AWS, Kubernetes and messaging platforms Kafka, MQ.
• Hands-on expertise in system design, application development, testing, and ensuring operational stability.
• Experience integrating LLMs, prompt/context engineering, and working with AI agent frameworks such as Langchain, LangGraph, Autogen, MCPs, and A2A.
• Proficiency in automation and continuous delivery practices and experience in building resilient, high-availability applications.
• Strong knowledge of all phases of the Software Development Life Cycle and software engineering using AI technologies.
• Advanced understanding of agile methodologies, including CI/CD, application resiliency, and security.
• Proven development lead experience in requirements gathering, task decomposition, estimation, delivery planning, testing, and user acceptance testing.
• Deep knowledge of design principles, data organization, and performance optimization.

• Practical experience with large datasets and query performance optimization.