
at J.P. Morgan
Bulge Bracket Investment BanksPosted 4 days ago
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**Lead Software Engineer - Full Stack/Generative AI/Large Language Models** utmost importance in our Consumer & Community Banking group. You'll spearhead software solutions, code development, and team AI-tool adoption. Key responsibilities include driving AI-assisted coding, test strategy acceleration, and solution-oriented vendor evaluations. Proven software engineering experience (5+ years), AI-assisted tool proficiency, and hands-on generative AI/LLM work are crucial. Requirements include advanced programming skills (Java, Python), cloud platforms (AWS, GCP, Azure), and familiarity with AI/ML frameworks (TensorFlow, PyTorch).
- Compensation
- Not specified USD
- City
- Not specified
- Country
- United States
Currency: $ (USD)
Full Job Description
Location: Plano, TX, United States
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 Consumer & Community Banking, 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 break down technical problems
- Develops secure 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
Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
Required qualifications, capabilities, and skills:
- Formal training or certification on software engineering concepts and 5+ years applied 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
- Advanced proficiency in programming languages (Java, Python, C#, etc.)
- Hands-on work with Large Language Models (LLMs) and generative AI.
- Familiarity with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face).
- Experience with distributed systems and cloud platforms (AWS, GCP, Azure).
- Expertise in microservices, RESTful APIs, and database technologies (relational/NoSQL).
- Familiarity with containerization tools (Docker, Kubernetes, Helm).
- Experience with performance testing tools (JMeter, Blazemeter) and Chaos Monkey Testing.
- Skilled in development and testing tools and frameworks (JUnit, UDF, Tophat, Cucumber, Groovy, Postman, REST Assured, Eclipse, Maven, Jenkins, IntelliJ).
- Cloud certification (AWS, GCP, Azure).
- Practical cloud-native development experience.
- In-depth knowledge of the financial services industry and their IT systems.
- Experience in creating and executing performance and chaos test scripts.
- Experience in or understanding of A/B Testing, Chaos Monkey Testing, Engineering principles.
- Effective communication across teams and management, with a proactive approach to process improvement.
- Strong system design, application development, and operational stability skills.



