Lead Software Engineer - AWS with Terraform

Partner closely with product, operations, security, and controls stakeholders, and help drive design quality and operational excellence for production workloads.

As a Lead Software Engineer at JPMorgan Chase within Cloud Foundation Services, you will lead within the team and domain by owning features and services end-to-end, guiding designs for moderately complex initiatives, and setting expectations for engineering quality and operational rigor.

Job Responsibilities


* Lead the design and implementation of key components of a public cloud platform, primarily on AWS.


* Develop secure, high-quality production code and infrastructure automation (primarily in Python and Terraform), and review and debug code written by others to ensure correctness, performance, and maintainability.


* Influence product design, application functionality, and technical operations within the team and domain by proposing pragmatic architectures, tradeoffs, and standards aligned to firm SDLC, security, and controls expectations.


* Partner with operations, SRE, security, risk, and controls stakeholders to deliver compliant solutions, improve observability, reduce operational toil, and ensure audit-ready processes and artifacts.


* Drive automation and CI/CD improvements, including pipeline reliability, quality gates, testing strategy, and repeatable environment provisioning to support safe and fast delivery.


* 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.


* Use AI-assisted developer tools, including GitHub Copilot and Microsoft Copilot, to accelerate routine engineering tasks (for example, scaffolding, small utilities, repetitive patterns, test generation, refactoring suggestions, and first-pass documentation), while ensuring all outputs are validated and refined to meet production and security standards.


* Define and reinforce safe team usage patterns for AI-assisted development, including verification expectations (correctness, security implications, licensing/IP considerations, and compliance) and adherence to firm controls (for example, avoiding sensitive data in prompts and ensuring reviews and approvals occur before merge and release).

Required Qualifications, Capabilities, and Skills


* Formal training or certification on software engineering concepts and 5+ years applied experience.


* 4+ years of professional e...