Live opening · Posted 7 days ago

Infrastructure Cloud Engineer - DevOps, Python, Platform engineer- Lead Software Engineer

JPMorgan Chase · Jersey City, NJ, United States | Plano, TX, United States
Oracle
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At a glance

The key details from the original listing.

Posted 7 days ago
CompanyJPMorgan Chase
LocationJersey City, NJ, United States | Plano, TX, United States
SourceOracle
Listed7 days ago

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About the role

Description supplied by the original job listing.

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 Technology, 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 break down technical problems
Develops secure high-quality production code, and reviews and debugs code written by others
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.
Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
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
Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Production Kubernetes depth — cloud-managed and on-prem. Runs and troubleshoots K8s at the platform layer, not just "deploys to it": cluster add-ons and their failure modes (cert-manager, admission control, policy-as-code, GitOps, Helm, ingress & load-balancer controllers), RBAC, and control-plane, webhook issues.
AWS at platform scale, multi-account. EKS, networking (VPC, load balancing, DNS), IAM, KMS secrets, and managed data stores. Fluent across resiliency patterns generally — multi-region, active active, active passive, failover, and cell-based designs.
Infrastructure-as-Code — Terraform required. Solid hands-on Terraform: module-based, disciplined plan, apply, and safe change management.
CI/CD & progressive delivery. End-to-end pipeline ownership — blue, green and cell-based rollouts, GitOps, artifact build, and orchestration (e.g., Spinnaker, Jenkins) — with strong safe-rollout and rollback judgment.
Production operational stability, SRE mindset. Incident response, root-cause analysis, resiliency, observability-driven debugging, reducing toil, and hardening production.
Some coding experience for internal tooling. Able to write scripts/automation and small internal tools (language-agnostic) to improve the platform — not a deep hands-on IC requirement, just practical coding fluency.
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
Proficient in all aspects of the Software Development Life Cycle
Preferred qualifications, capabilities, and skills
IAM customer-authentication knowledge — ForgeRock (AM, DS) or PingFederate, OAuth2, OIDC, SAML, PKI cert lifecycle. Helpful, but a strong platform engineer who ramps on our stack is fine.
Resiliency chaos engineering (Game Days, fault injection).
Secrets management (Vault, KMS, Secrets Manager). Observability depth (Splunk, Dynatrace).
Managed database ops (Aurora, RDS, DB-change automation).
On-prem → cloud migration experience.
"Platform-as-a-product" experience — owning a platform other engineering teams depend on.
Certs as signal (not gates): AWS Solutions Architect, DevOps Pro, CKA, CKAD, ForgeRock, Ping.

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