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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Software Engineer: Vice President - **Company:** JPMorgan Chase & Co. - **Location:** New York, NY, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Automation of Tests, Cloud Computing, Software Quality, Code Review, Software Debugging, Middleware, Identity and Access Management, Subnetting, Spring Framework, PostgreSQL, Machine Learning, Software Tools, Secure Coding, Software Engineering, Software Systems, Systems Architecture, Strategies of Testing, Toolchain, Large Language Models, Spring-boot, Amazon Virtual Private Cloud (VPC), Production Code, Cloudwatch, Restful APIs, Code Restructuring - **Published:** July 1, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/27655869/Lead-Software-Engineer-Vice-President-New-York-New-York-7463 ## About the Role * Formal training or certification in software engineering concepts and 5+ years of applied experience in software development * Extensive experience designing, developing, debugging, and maintaining applications in a large corporate environment. * Hands-on practical experience delivering system design, application development, testing, and operational stability * Hands-on experience building AI Agents and leveraging AI Powered tools, RAG pipelines and LLM API's. * Proficient in coding in one or more programming language(s): Java * Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) * Strong hands-on experience with Java, Spring, and Spring Boot * Experience designing and implementing REST APIs * Strong AWS experience: ECS and Lambda, networking and core services knowledge (ALB, NLB, GWLB; VPC, subnets, security groups, IAM, CloudWatch) * 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 Preferred qualifications, capabilities, and skills * Familiarity with middleware technologies * Hands on AWS Services experience with ECS, Lambda Aurora Postgres * Exposure to cloud technologies * Cloud Certification * Anthropic Claude Code experience ## Description Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products., * Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems * Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems * Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development * Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems * Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture * Contributes to software engineering communities of practice and events that explore new and emerging technologies * 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. ## Related Videos - [Can This Elephant Dance? 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