JOB DESCRIPTION
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 JPMorganChase within the Asset and Wealth Management, 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
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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
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Develops secure and high-quality production code, and reviews and debugs code written by others
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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.
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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.
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Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
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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
- Formal training or certification on software engineering concepts and 5+ years applied experience
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Hands-on practical experience delivering system design, application development, testing, and operational stability
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Experience in building applications using LLM driven code generation such as Claude Code or Microsoft copilot
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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.
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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
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Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
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Practical knowledge of web application development on AWS
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Good Experience in Java development, cloud deployments and in continuous delivery and DevOps tooling
Preferred qualifications, capabilities, and skills
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Experience in building, evaluating and deploying Machine learning Models into Production
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Experience in integration of standard AI/ML/LLM software solutions, design, development, and technical troubleshooting.
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Experience working with Large Language Models (LLM)/GenAI technology like OpenAI API, (GPT models), HuggingFace models etc. having solid understanding of Transformers architecture.
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Experience in Natural Language Processing and NLP tools and libraries like Spacy.
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