Lead Software Engineer - FinOps, Cloud Platform

At Chase International Consumer Bank, we are building a digital bank from the ground up, combining the agility of a modern engineering organization with the scale of a trusted global brand. As a Lead Software Engineer - FinOps (Vice President) within JPMorganChase International Consumer Bank, you will be a hands-on engineering leader helping Chase UK build and run cloud-native capabilities that improve unit economics, reliability, and platform eMiciency across our public cloud footprint, primarily AWS.

You will design and deliver engineering solutions that make cloud financial management actionable through software, automation, and policy-as-code guardrails. You will partner closely with application, platform, and SRE/DevOps teams to influence architecture and delivery practices, and to embed strong engineering standards into day-to-day workflows.

You will operate in a modern cloud stack (AWS, Kubernetes/EKS, Terraform, event-driven components) and drive improvements across Kubernetes engineering, automation runbooks, and developer experience. Go is the primary language for application development in this role, with Python as a valuable secondary skill for tooling and automation. Good-to-have platform tooling includes GitHub Actions, Argo CD, and control-plane automation approaches like Crossplane, as well as strong AWS solutions architecture depth.

Job responsibilities:

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Design, build, and maintain backend services and automation in the cloud financial management space. The software you deliver will support cost tracking, allocation, governance, compliance, and reporting for teams running workloads on AWS (primary) and GCP (secondary).

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Deliver production-grade software with strong engineering discipline, including clear design, code reviews, secure coding practices, and appropriate automated testing.

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Apply solid Kubernetes fundamentals to build practical solutions and standards, including resource requests and limits, scaling behaviour, workload placement, and safe operation of shared clusters.

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Create dashboards and engineering-facing views that connect usage, performance, and scaling Behaviour to cost outcomes, and help teams act on the results.

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Build Kubernetes automation that improves eMiciency and reduces waste using proven tools and patterns such as Karpenter for node provisioning and right-sizing, and KEDA for event-driven scaling, along with custom automation where needed.

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Contribute to platform management and platform development practices, including cluster lifecycle and upgrades, platform reliability, standard templates, paved paths, and developer self-service capabilities.