
Lead Software Engineer - Cloud / GCP Engineer
JPMC · Plano, TX, United States
Strong hiring record · median 28 days open
All reasons
In its favour
- Still listed on the employer's own board
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 platform, 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
- 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
- Leads the architecture and hands-on delivery of GCP foundational platform capabilities (landing zones, org/folder/project hierarchy, networking, shared services).
- Builds and maintain reusable automation and paved roads (Terraform modules, reference architectures, CI/CD enablement) that accelerate secure onboarding.
- Owns GCP security guardrails: IAM/role engineering, service account patterns, IAM Conditions, org policies, and deny policies.
- Designs and implements identity federation (OIDC/SAML, Workforce Identity Federation, Workload Identity Federation) and enable IAM governance/audit readiness through automation and evidence patterns.
- 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.
- 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
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Strong experience with GCP IAM and identity (role/permission modeling, service accounts, federation patterns, access governance).
- Hands-on expertise with key GCP services such as Cloud Run/Cloud Functions, Pub/Sub, and GKE.
- Proficiency in Terraform and programming/scripting in Python or Go (automation, tooling, CI/CD integration).
- Experience implementing guardrails at scale (IAM Conditions/deny policies, policy-as-code, centralized logging/audit, key management patterns).
- Demonstrated ability to deliver secure, compliant solutions and influence technical decisions across cross-functional teams.
- 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
- Experience with AWS and/or Azure (multi-cloud operating models and patterns).
- Strong containerization/orchestration experience (Docker, Kubernetes), including production-grade GKE operations.
- Solid understanding of OAuth2, OIDC, and SAML; secure service-to-service identity patterns.
- Good understanding of LLM and other AI/ML frameworks which can be used in AIOPS
- Relevant certifications (e.g., Google Professional Cloud Architect and/or Professional Cloud Security Engineer).
Skills
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