Lead Software Engineer - Backend Lead

JPMorgan Chase & Co.; Plano (TX); On-site; USD 140,000 - 170,000; Full time

Job summary

JPMorganChase’s Corporate Sector Enterprise Technology team seeks a Lead Software Engineer to design, deliver secure, scalable technology products and drive AI-assisted engineering practices across the SDLC. You will lead high-impact development efforts, mentor engineers, and collaborate across domains to meet business objectives.

The role emphasizes responsible AI usage, secure coding standards, and building resilient systems within a fast-paced agile environment in Plano, TX.

Qualifications

• Formal training or certification in software engineering concepts and 5+ years applied experience.
• 10+ years of software development experience.
• Demonstrated experience leading effective use of approved AI-assisted software development tools with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Strong knowledge and practical experience with Java, Spring, RESTful APIs, RabbitMQ, Kafka and Microservices architectures.
• Experience with version control systems such as Git and workflow management systems such as JIRA or ServiceNow.
• 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
• Practical knowledge of CI/CD, Jenkins, and source code management tools such as Git and Bitbucket.
• Experience with using relational database like Oracle
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., Cloud, artificial intelligence, machine learning etc.)

Responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes
• Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect

Skills

Team leadership

Agile / Scrum

Responsible AI use

Communication

Education

Software engineering certification

Tools

Java

Spring

RESTful APIs

RabbitMQ

Kafka

Microservices

Git

JIRA

ServiceNow

CI/CD

Jenkins

Terraform

Kubernetes

Oracle

Job description

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 Lead Software Engineer at JPMorganChase within the Corporate Sector Enterprise Technology team, you will be an experienced member of an agile team. Your responsibilities include designing and delivering secure, stable, and scalable technology products. Additionally, you will implement critical technology solutions across multiple technical areas to support various business functions and help achieve the firm’s business objectives.

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
• Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• 10+ years of software development experience.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Strong knowledge and practical experience with Java, Spring, RESTful APIs, RabbitMQ, Kafka and Microservices architectures.
• Experience with version control systems (e.g., Git) and workflow management systems such as JIRA or ServiceNow.
• 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
• Practical knowledge of CI/CD, Jenkins, and source code management tools such as Git and Bitbucket.
• Experience with using relational database like Oracle
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., Cloud, artificial intelligence, machine learning etc.)

Preferred qualifications, capabilities, and skills

• Exposure to cloud technologies (AWS, Azure, GCP) or DevOps practices.
• Exposure to Jenkins CI/CD, Terraform, Kubernetes.
• Experience in Identity and Access Management, preferably Privileged Access Management.