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:
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).
Deliver production-grade software with strong engineering discipline, including clear design, code reviews, secure coding practices, and appropriate automated testing.
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.
Create dashboards and engineering-facing views that connect usage, performance, and scaling Behaviour to cost outcomes, and help teams act on the results.
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.
Contribute to platform management and platform development practices, including cluster lifecycle and upgrades, platform reliability, standard templates, paved paths, and developer self-service capabilities.
Build and maintain CI/CD pipelines for services and platform components to enable repeatable, low-risk releases, with strong visibility and rollback practices.
Work closely with application teams, SRE/DevOps, and leadership to drive adoption of eMicient cloud patterns, and to ensure improvements are delivered and sustained in production.
Bring strong cloud financial management knowledge to daily engineering work, including cost allocation and tagging hygiene, anomaly investigation, budget and forecast inputs, and measurement of realized impact.
Required qualifications, capabilities, and skills:
Strong hands-on software engineering experience building and operating backend services in production, with a focus on reliability, maintainability, and operational readiness.
Go as the primary language for application development; Python is a strong for tooling, scripting, and automation.
Strong Kubernetes fundamentals and practical experience running workloads on Kubernetes (ideally EKS), including debugging, scaling, performance tuning, and safe operation of shared clusters.
Strong knowledge of cloud financial management and cost governance on AWS, including cost allocation, tagging strategy, anomaly investigation, budgeting and forecasting inputs, and measuring realized savings.
Hands-on experience with AWS cost optimization levers beyond discount programs, including right-sizing, scaling strategies, storage lifecycle choices, and architecture decisions that improve unit economics.
Experience with infrastructure as code and control-plane automation, including Terraform and Crossplane.
Working knowledge of AWS networking and distributed systems fundamentals needed to build scalable and cost-aware systems.
Strong DevOps and SDLC practices, including code reviews, test automation, secure coding practices, and operational ownership.
Experience building and maintaining CI/CD pipelines for services and platform components, including GitHub Actions.
Strong numerical and analytical skills; comfortable working with cost and usage datasets to spot trends and drive practical engineering changes.
Strong communication skills and the ability to partner eMectively across platform, application, and operations teams to drive changes through to production
Preferred qualifications, capabilities, and skills:
Experience with Kubernetes eMiciency and scaling tooling such as Karpenter and KEDA.
Experience with Kubernetes and cloud cost visibility and optimization tools such as Kubecost, AWS Cost Explorer, AWS Budgets, AWS Cost and Usage Reports (CUR), AWS Compute Optimizer, and CloudWatch.
Familiarity with broader cost governance and observability tooling (for example Grafana, QuickSight, Flexera) and the ability to turn data into actionable engineering work.
GitOps and deployment tooling exposure such as Argo CD.
Exposure to GCP billing and cost management concepts in addition to AWS
