at J.P. Morgan
Bulge Bracket Investment BanksPosted 4 days ago
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**Lead Software Engineer** in Hyderabad, driven to impact your career. As a senior-level tech lead, leverage 5+ years of software engineering experience to creatively solve complex problems and deliver high-quality, secure code. Your expertise spans full SDLC, agile methodologies (CI/CD), and AI-assisted software development tools. Collaborate cross-functionally, driving team adoption of AI for enhanced code quality and operational stability. Lead vendor evaluations and define architectural designs. Deepen your industry knowledge in financial services IT systems, while gaining practical cloud-native experience. Proven leadership and advanced programming skills required.
- Compensation
- Not specified
- City
- Not specified
- Country
- India
Currency: Not specified
Full Job Description
Location: Hyderabad, Telangana, India
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 JPMorgan Chase within the Consumer and community banking technology team, 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 firms business objectives.
Job responsibilities
As a Lead Software Engineer at JPMorgan Chase within the Consumer and community banking technology team, 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 firms 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
- Develops secure and 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 evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Required qualifications, capabilities, and skills
- A. Formal training or certification on software engineering concepts and 5+ years applied experience ( NAMR/APAC India/ LATAM/ Hong Kong)
B. Formal training or certification on software engineering concepts and advanced applied experience (EMEA/LATAM-Brazil)
C. Singapore follow local country guidance - Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s)
- 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
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- In-depth knowledge of the financial services industry and their IT systems
- Practical cloud native experience
