Lead Software Engineer – Cloud Strategy

JPMorgan Chase & Co.; Plano (TX); On-site; USD 150,000 - 230,000; Full time

Job summary

JPMorgan Chase & Co. invites a Lead Software Engineer to partner with the Consumer and Community Banking - Deposits team. You will shape cloud architecture, drive AI integration, and lead initiatives that ensure secure, scalable, and cost-aware technology delivery.

You will champion AWS-based solutions, resilience, observability, and engineering practices across multiple product areas while translating technical strategy into actionable leadership narratives for cross-functional teams.

Qualifications

• 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.

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.

Skills

AWS expertise

Cloud architecture

Executive communication

Software engineering concepts

Systems thinking

AI integration

Automation

Code review tools

Tools

AI-assisted development tools

Automation tooling

Code review tools

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 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.

Preferred qualifications, capabilities, and skills

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