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JPMC Candidate Experience page
Lead Software Engineer - Java Fullstack
JPMC Candidate Experience page
Bengaluru•On-site•5-8 Yrs•1 day ago
Job description
Overview
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
Responsibilities
- Executes creative 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
- 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
- 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
- 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
Qualifications
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Expertise in JAVA , Java Spring, SQL and NoSQL DBs
- Resilience & Observability: Circuit breakers, bulkheads, metrics, tracing, alerting, chaos exercises. Cloud: AWS/Azure/GCP (infrastructure as code, autoscaling, caching, managed databases)
- AI/LLM: Model serving, retrieval augmentation, prompt management, safety and evaluation frameworks
- Hands-on practical experience in system design, application development, testing, and operational stability
- Proficient in coding in one or more languages. Practical cloud native 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
Nice to have
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)