Lead Software Engineer – Cloud Strategy

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As a Lead Software Engineer at JPMorganChase within the Consumer and Community Banking - Deposits team, 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

• Shape the end-to-end AWS cloud architecture strategy across all product components.
• Advance the resiliency strategy — multi-region, active-active, failover/failback, and DR.
• Strengthen cloud cost strategy and optimization across the product, Evolve the automation and infrastructure-as-code strategy.
• Mature AI integration across engineering and product workflows, Drive scalability strategy to meet growth and peak-demand requirements.
• Harden cloud security strategy and regulatory-grade controls.
• Deepen observability and chaos engineering practices.
• Raise the bar on shared architectural standards and decision-making across teams.
• Sharpen how complex technical strategy is distilled into leadership-facing narratives.
• 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.
   

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
•  Deep, broad AWS expertise across compute, data, networking, and security, with proven production architecture work.
• Systems thinking — reasoning about trade-offs, failure modes, and dependencies across an entire product.
• Strategic command of cost, scalability, automation, and AI integration as connected levers.
• Hands-on depth to validate and prototype ideas, not just advise.
• Executive communication and rigorous, independent judgment in a regulated, high-stakes environment.
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• 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

   

• In-depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience