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Salary
≈ $121k – $242k per year (Estimated)
Location
In office (Tampa)
Seniority
Middle · 3+ years exp
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Confirmed on the employer's own hiring board on Nov 4, 2026. First seen by Alion on Oct 5, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

You belong to the top echelon of talent in your field. At one of the world's most iconic financial institutions, where infrastructure is of paramount importance, you can play a pivotal role.

As an Infrastructure Engineer III at JPMorganChase within the Payments Technology Strategic Initiative Office group, you utilize strong knowledge of software, applications, and technical processes within the infrastructure engineering discipline. Apply your technical knowledge and problem-solving methodologies across multiple applications of moderate scope.

Job responsibilities

  • Centrally manage the Payments SIO FinOps book of work with an AWS first mandate, partnering with Payments CTO Infrastructure Managers (IMs) and application teams to deliver measurable optimization outcomes across AWS (primary focus), on-prem (GKP, GAP, VSI, GVP, GOS), and, when relevant, SaaS data platforms (Snowflake, Databricks) as a secondary, good-to-have scope.
  • Own and maintain a centrally managed FinOps optimization backlog for Payments, including intake, triage, prioritization, and execution tracking, and run a repeatable operating cadence for identification → sizing → approval → execution → validation → value realization with clear ownership, dependencies, and target dates.
  • Applies technical knowledge and problem-solving methodologies to projects of moderate scope, with a focus on improving data and systems running at scale, and ensures end to end monitoring of applications
  • Uses enterprise-authorized AI capabilities within the work environment to accelerate monitoring and capacity analysis and documentation, validating outputs and handling operational data according to sensitivity and security requirements.
  • Drives the daily activities supporting the standard capacity process applications and partners with application and infrastructure teams to identify potential capacity risks and govern remediation statuses
  • Accountable for making significant decisions for a project consisting of multiple technologies and applications
  • Applies reuse-first, AI-assisted approaches to identify recurring capacity risks and improve remediation workflows, ensuring changes are validated and aligned to resiliency and security expectations.

Required qualifications, capabilities, and skills

  • Formal training or certification on infrastructure engineering concepts and 3+ years applied experience
  • Strong infrastructure-as-code (IaC) experience using Terraform
  • Strong knowledge of one or more infrastructure disciplines such as: hardware, networking terminology, databases, storage engineering, deployment practices, integration, automation, scaling, resilience, and performance assessments
  • 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.
  • Strong knowledge of one or more scripting languages
  • Experience with multiple cloud technologies (ability to operate in and migrate across public and private clouds)

Preferred qualifications, capabilities, and skills

  • Demonstrated hands-on experience delivering AWS FinOps optimization outcomes in a large-scale enterprise environment, translating us age/spend/utilization data into executed engineering changes with measurable results

  • Proficiency or working knowledge using firmwide infrastructure us age/spend/utilization tooling such as iHub, CloudVision, ClaroUtil to identify opportunities, produce actionable insights, and track outcomes

  • Desirable experience optimizing Snowflake and Databricks consumption and cost (workload patterns, sizing, scheduling, governance).

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