Senior Lead Software Engineer

JPMorganChase•Plano, TX

About The Position

Executes software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems. 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. Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development. Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture. Contributes to software engineering communities of practice and events that explore new and emerging technologies.

Requirements

Formal training or certification on software engineering concepts and 5+ years applied experience.
8+ years of software development experience.
Demonstrated experience leading effective use of approved AI-assisted software development tools.
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 understanding of computer science fundamentals, algorithms, and data structures.
Strong knowledge and practical experience with Java, Spring Framework (Spring Boot, Spring MVC, Spring Data), RESTful APIs, Kafka, Postgres SQL and Microservices architectures.
Practical knowledge of CI/CD, Jenkins, and source code management tools such as Git and Bitbucket.
Proficiency in designing and implementing data models for relational databases.
Experience with using relational database like Postgres SQL.
Experience working on Cloud platform (AWS/GCP/Azure/ Kubernetes).

Nice To Haves

Experience in Identity and Access Management.
Experience to cloud services such as AWS S3, EC2, EKS, IAM, and Lambda.
Experience in Cloud and Container based development (Gaia, Kubernetes).

Responsibilities

Executes software solutions, design, development, and technical troubleshooting.
Drives team adoption of enterprise-authorized AI-assisted engineering practices.
Establishes consistent validation standards (secure coding, peer review, automated testing).
Promotes reuse of effective patterns across the team.
Applies knowledge of tools within the Software Development Life Cycle toolchain.
Creates secure and high-quality production code.
Maintains algorithms that run synchronously with appropriate systems.
Produces architecture and design artifacts for complex applications.
Ensures design constraints are met by software code development.
Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements.
Contributes to software engineering communities of practice and events.