Lead Software Engineer - (Golang, AWS, Terraform, FinOps)
JPMorgan Chase & Co., Bengaluru, Karnataka, India
JPMorgan Chase & Co., Bengaluru, Karnataka, India
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.
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).
including clear design, code reviews, secure coding practices, and appropriate automated testing.
standards, including resource requests and limits, scaling behaviour, workload placement, and safe operation of shared clusters.
performance, and scaling Behaviour to cost outcomes, and help teams act on the results.
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.
including cluster lifecycle and upgrades, platform reliability, standard templates, paved paths, and developer self-service capabilities.
enable repeatable, low-risk releases, with strong visibility and rollback practices.
adoption of eMicient cloud patterns, and to ensure improvements are delivered and sustained in production.
including cost allocation and tagging hygiene, anomaly investigation, budget and forecast inputs, and measurement of realized impact.
backend services in production, with a focus on reliability, maintainability, and operational readiness.
for tooling, scripting, and automation.
Kubernetes (ideally EKS), including debugging, scaling, performance tuning, and safe operation of shared clusters.
including cost allocation, tagging strategy, anomaly investigation, budgeting and forecasting inputs, and measuring realized savings.
programs, including right-sizing, scaling strategies, storage lifecycle choices, and architecture decisions that improve unit economics.
including Terraform and Crossplane.
needed to build scalable and cost-aware systems.
secure coding practices, and operational ownership.
components, including GitHub Actions.
usage datasets to spot trends and drive practical engineering changes.
platform, application, and operations teams to drive changes through to production
and KEDA.
such as Kubecost, AWS Cost Explorer, AWS Budgets, AWS Cost and Usage Reports (CUR), AWS Compute Optimizer, and CloudWatch.
example Grafana, QuickSight, Flexera) and the ability to turn data into actionable engineering work.
Pay not posted
Posted Oct 13, 2026
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