Lead Infrastructure Engineer — On Prem OpenShift Platform

JPMorganChase•Jersey City, NJ

2d•Onsite

About The Position

We're looking for a talented, senior engineering professional ready to take their career to new heights at one of the world's most influential companies. As a Lead Infrastructure Engineer at JPMorgan Chase within Enterprise Technology Compute Infrastructure Platforms team, you will design and build the software layer that makes our OpenShift platform usable at enterprise scale. You will focus on private cloud solutions that enable Kubernetes-based hypervisor and container platforms on OpenShift, with the goal of delivering a consistent end-user experience across on-premises and public cloud environments. You will develop self-service workflows, platform APIs, controllers/operators, integrations, automation services, and developer/platform tooling in partnership with infrastructure engineering and key platform stakeholders.

Requirements

Formal training or certification on infrastructure engineering concepts and 5+ years applied experience (mandatory requirement).
Experience delivering production services.
Demonstrated proficiency building production systems in Go and/or Python (strong proficiency in at least one language).
Demonstrated knowledge of distributed systems fundamentals (API design, concurrency, failure modes, idempotency, retries/timeouts, and observability).
Hands-on experience with Kubernetes and containers in production (Kubernetes primitives, client libraries, manifests, Helm/Kustomize concepts, and deployment patterns).
Experience building platform software for OpenShift/Kubernetes environments (e.g., platform APIs, automation services, and developer/platform tooling).
Experience implementing CI/CD practices and toolchains for platform software (testing strategies, release versioning, and rollback), including GitOps patterns.
Experience with GitOps and pipeline tooling (e.g., Argo CD and Tekton/Jenkins/GitHub Actions, or equivalent).
Experience applying secure engineering practices in platform services (e.g., authN/authZ, secrets handling, and vulnerability remediation workflows).
Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.

Nice To Haves

OpenShift development and/or operations familiarity (Operators, RBAC/SCC nuances, routes/ingress patterns).
Operator/Controller development experience, especially Go + controller-runtime patterns.
Experience building internal developer platforms (portals, scaffolding, golden paths, policy-as-code, automation frameworks).
Security-minded engineering experience (authN/authZ, secrets handling, SBOM/signing concepts, vulnerability remediation workflows).
Experience with multi-cluster and multi-environment platform strategy, enabling consistent user experiences across on premise and public cloud.
Passion for innovation, AI-assisted engineering, and continuous improvement practices that measurably improve quality and delivery speed.

Responsibilities

Design and implement platform services that enable workload onboarding and lifecycle management (provisioning, policy/guardrails, quotas, templates, golden paths).
Build Kubernetes-native automation, including custom controllers/operators where appropriate.
Integrate platform services with identity, secrets, policy, observability, and CMDB/service-catalog patterns as required.
Develop tools and services for multi-cluster operations, cluster onboarding, configuration standardization, and compliance reporting.
Implement CI/CD for platform software with engineering rigor, including testing, code review, static analysis, release versioning, and rollback strategies.
Collaborate with infrastructure engineers to define reliability and performance requirements and to reduce operational friction through automation and clear interfaces.
Deliver secure, high-quality production code that supports scalable, reliable private cloud infrastructure services.
Produce architecture and design artifacts for complex platform components and ensure constraints are met throughout implementation.
Document platform capabilities through high-quality documentation, examples, and reference implementations to drive adoption.
Uses enterprise-authorized AI capabilities within the work environment to accelerate analysis of complex infrastructure signals and documentation of mitigation options, validating outputs and handling operational data according to sensitivity and security requirements.
Leads reuse-first adoption of AI-assisted practices across delivery and automation routines to reduce recurring issues, ensuring changes are validated, traceable and auditable, and aligned to resiliency and security expectations.