Lead Software Engineer - Python Full stack developer
JPMorgan Chase · Hyderabad, India · 21h ago
Staff / Lead / PrincipalOn-siteSoftware Engineering
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As a Lead Software Engineer at JPMorgan Chase within the Infrastructure Platforms - Networks, 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 business functions in support of the firm’s business objectives.
Job responsibilities
As a Lead Software Engineer at JPMorgan Chase within the Infrastructure Platforms - Networks, 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 business functions in support of the firm’s business objectives.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Leads the technical design of features, translating business requirements into scalable, secure, and maintainable solutions while defining architecture, interfaces, and implementation approaches.
- Provides technical leadership to the engineering team by guiding implementation, reviewing designs and code, resolving technical blockers, and ensuring high-quality delivery aligned with engineering standards.
- Executes standard software solution, design, development, and technical troubleshooting
- Writes secure and high-quality code using the syntax of at least one programming language with limited guidance
- 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.
- Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
- Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity
- Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
- Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Proficient experience in Python, with hands-on expertise in Django or Flask or FastAPI.
- Experience with React and AngularJS
- Knowledge on Astronomer/Airflow. Strong knowledge of API development.
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs
- Solid understanding of agile methodologies, application resiliency, and system integration.
- Knowledge of code maintainability, including source control (Bitbucket or similar), code branching strategies, and deployment in cloud environments.
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- 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
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
- Good knowledge of networking concepts, a basic CCNA certification
- Experience with cloud-based technologies, knowledge of Kubernetes , Dockers