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Salary
≈ $158k – $324k per year (Estimated)
Location
In office (Plano)
Seniority
Staff · 5+ years exp
Visa
H-1B filings in 12 months: 3,429 · for this role: 1,686 · green card filings: 933

Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Oct 22, 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.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JP Morgan Chase within the Cybersecurity and Technology Controls line of business, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

This role combines software engineering, DevOps, and cloud engineering. Our technology set is wide and keeps changing, so you will be expected to pick up new services quickly and automate wherever you can.

Job Responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leverages DevOps tools to build, deploy, and operate a cloud-based orchestration platform, infrastructure as code, and automated compliance capabilities, keeping delivery automated and elastic
  • Leads the design and development of new cloud implementations, with strategies for end-to-end automation, architecture design, performance and monitoring, proofs of concept, and transition to operations
  • Creates automated functional, performance, resiliency, and end-to-end tests and makes them required quality gates in the pipeline
  • Regularly provides technical guidance and direction to the business and its technical teams, mentors engineers, and leads communities of practice across Software Engineering
  • Learns new technologies and services quickly as the platform evolves, and delivers production-ready work on them with minimal ramp-up
  • Builds the tooling that lets an environment owner diagnose why their environment is unhealthy in production and fix it themselves

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced in one or more programming language(s): Java, Python, or Go
  • Proficient in all aspects of the Software Development Life Cycle
  • Practical cloud native experience
  • Expertise with AWS infrastructure such as networking, EC2, Lambda, serverless solutions, VPC, Route 53, auto scaling, Transit Gateway, API Gateway, Step Functions, Secrets Manager, storage services, and containers (EKS, ECS, Fargate)
  • Proficient in core concepts for networking, public cloud architecture, and Infrastructure as Code (IaC), with hands-on Terraform experience
  • Expertise in designing and developing complex cloud architectures, deploying scalable solutions, and applying DevOps practices, including creating and managing CI/CD pipelines, application resiliency, and triaging issues
  • Testing proficiency from unit to end-to-end, with tools such as Cucumber (functional testing), JUnit 5 or pytest (unit testing), JMeter (performance testing), and Gremlin (resiliency testing)
  • Experience with SQL and NoSQL databases
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.

Preferred qualifications, capabilities, and skills

  • Experience designing, deploying, and operating production workloads on AWS with Terraform, including reusable modules, state management, and multi-environment deployments
  • Experience using AI-assisted software development tools such as Claude Code or GitHub Copilot for coding, testing, and troubleshooting
  • Experience in microservice and API development, with working proficiency in both Python and Java
  • Experience with observability tools such as Splunk, Grafana, or Dynatrace, and with data streaming platforms such as Kafka
  • AWS certification, such as Solutions Architect, Developer, or DevOps Engineer
  • Knowledge of the financial services industry or another regulated environment
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