Sr Lead Software Engineer
Software Engineering
Bengaluru, Karnataka, India
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 Commercial & Investment Bank's Research Technology space, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies.
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 15+ years applied experience.
- Write maintainable & testable code in Java and/or Python that is consistent with cloud related architecture principles.
- Experience working in Unix. Defect Management (JIRA or equivalent).
- Build Cloud Native applications from a domain driven design and micro-services architecture perspective supporting multiple API versions.
- Knowledge of cloud concepts regarding data storage and data processing.
- Developing and implementing highly responsive user interface components using react concepts.
- Collaborate to design solutions including conceptual, logical and physical data models.
- Participate & effectively contribute in scrum ceremonies with the product owner and scrum team.
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
- Experience with Test driven development, Continuous Integration and Deployment practices and tools (Jenkins, Git-Stash)
Preferred qualifications, capabilities, and skills
- Experience working on Databricks/Snowflake.
- Experience in building Data Lakes using AWS and Hands-on experience in AWS Glue, AWS KMS etc.
- Experience in Spark leveraging Python or in-depth experience in Java.
- Experience in writing SQL queries
Lead and evolve our next generation data platform, using Java and Python to manage and optimize complex large scale data systems