Lead Software Engineer - Cloud

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 Corporate Sector – Infrastructure Platforms, 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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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
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Lead the design and implementation of platform services and infrastructure with an emphasis on architecture, integration patterns, and system reliability
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Develop, review, debug, and maintain secure, high-quality production code, applying engineering judgment to ensure it meets our standards regardless of whether it originates from you, a teammate, or an approved artificial intelligence tool
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Identify opportunities to eliminate or automate remediation of recurring issues to improve operational stability across applications and systems
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Lead design reviews and architecture discussions to evaluate solutions, strengthen technical quality, and support scalable delivery
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Partner with platform architecture, trust and authorization teams, and downstream IAM consumers to land coherent designs across organizational seams; Lead communities of practice across Software Engineering to increase awareness and adoption of new and leading-edge technologies
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Mentoring and coaching engineers through technical guidance
Required qualifications, capabilities, and skills
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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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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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Experience with Identity and Access Management platforms, role-based access control, or entitlement governance at scale
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Advanced proficiency in one or more programming languages, frameworks, or platforms such as Java, Spring, Go, Python, Terraform, or Kubernetes
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Practical cloud-native experience building and operating services on at least one public cloud provider, such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform
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Advanced understanding of agile methodologies such as continuous integration and continuous delivery, application resiliency, and security
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Ability to evaluate technical solutions with a customer-focused mindset and understand how engineering decisions impact users and business outcomes
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Strong communication skills with the ability to adapt messages for technical and non-technical audiences
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Responsible use of approved artificial intelligence tooling, with critical judgement to validate quality, correctness, security, and performance and experience with Terraform
Preferred qualifications, capabilities, and skills
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Experience working in financial services or another highly regulated technology environment with formal audit and control posture
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Experience contributing to public cloud platform services, developer platforms, or shared engineering capabilities
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Familiarity with responsible artificial intelligence use in engineering workflows, including secure handling of inputs and outputs
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Experience improving developer experience, platform reliability, or operational efficiency at scale