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求人JPMorgan Chase

Senior Lead Software Engineer - Java / AWS

JPMorgan Chase

Senior Lead Software Engineer - Java / AWS

JPMorgan Chase

Columbus, OH, United States, US

·

On-site

·

Full-time

·

1mo ago

必須スキル

AWS

Terraform

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan Chase within the Consumer and Community banking technology team, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

  • Engage with development team throughout agile sprints to develop software for reliability and scale, ensuring minimal refactoring or changes
  • Identify application patterns and analytics in support of better service level objectives. Design automated software and product upgrades, change management, and release management solutions.
  • Gain Experience in Operating Services in Public Cloud, Strong grasp of SRE principles; SLIs/ SLOs, error budgets, incident management, observability, and resilience patterns. Hands-on with observability and incident tooling, Proficiency with CI/CD and deployment strategies
  • Drive prioritized remediation programs across change/configuration, capacity/performance, dependency resilience, and code quality.
  • Troubleshoot priority and escalation incidents, facilitate blameless post-mortems and ensure permanent closure of incidents and subsequent problem tasks.
  • Establish comprehensive automated functional testing with dependable regression suites integrated into CI/CD to gate releases; improve reliability and speed through robust test data and include non-functional checks (performance, resilience, accessibility) in pre‑prod and readiness reviews.
  • Implement demand forecasting, load testing, and performance engineering in pre-prod; validate scale assumptions before peak events.
  • Run game days and chaos experiments to validate failover, degraded-mode operation, and dependency timeouts.
  • Embed shift‑left quality and partner with Product to mature testing practices: co‑define clear acceptance criteria and Definition of Ready/Done, align coverage to critical user journeys, and track quality KPIs (defect escape rate, automated coverage on key paths, change failure rate) tied to service objectives and release readiness.
  • Utilize platform and automation

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 12+ years applied experience
  • Extensive experience designing, deploying, and managing AWS infrastructure (VPC, EC2, ALB, Elastic Cache, Route 53, S3, IAM) using Terraform for automated, version-controlled provisioning.
  • Proficient in writing modular, reusable Terraform code for multi-environment infrastructure automation, state management, and CI/CD integration.
  • Hands-on experience deploying, scaling, and managing containerized applications on AWS EKS, including cluster setup, node groups, Kustomize, Helm charts, and service mesh integration.
  • Proven track record supporting production platforms with incident response, root cause analysis, troubleshooting, and cross-team collaboration to ensure high availability and reliability.
  • Skilled in designing and executing load, stress, and performance tests using JMeter and Blaze Meter to identify bottlenecks and optimize application performance.
  • Proficient in coding in one or more languages
  • Core Modern Java (Version 17 or higher) (Example: Streams, Multithreading, Collections, and Exception handling mechanism, Lamdas) or Python.
  • Strong development experience building RESTful APIs, microservices, and enterprise applications using Java and Spring Boot with a focus on scalability and maintainability.
  • Familiar with SRE principles including SLIs/SLOs/SLAs, incident management, post-mortems, automation, observability, and reliability engineering practices.
  • Experienced in leveraging Splunk, Datadog, and Dynatrace, Cloudwatch, X-Ray for log aggregation, real-time monitoring, alerting, APM, and performance troubleshooting in production environments.

Preferred qualifications, capabilities, and skills

  • Developer or Solutions Architect Level AWS Certification
  • Experience with any of these Observability tools: Splunk, Datadog, Dynatrace, or Grafana.
  • Experience with distributed databases like AWS DynamoDB, AWS RDS Aurora, Cassandra, and Terraform infrastructure-as-code.
  • Proficiency in multiple modern programming languages (JAVA, Python, SQL)
  • Proficient in AI-assisted coding workflows (Copilot, Claude Code) and collaborative, iterative development with AI tools.

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JPMorgan Chaseについて

JPMorgan Chase

JPMorgan Chase & Co. is an American multinational banking institution headquartered in New York City and incorporated in Delaware. It is the largest bank in the United States, and the world's largest bank by market capitalization as of 2025.

300,000+

従業員数

New York City

本社所在地

$500B

企業価値

レビュー

3.8

10件のレビュー

ワークライフバランス

3.2

報酬

4.1

企業文化

3.8

キャリア

3.0

経営陣

2.5

65%

友人に勧める

良い点

Good benefits and compensation

Supportive and collaborative environment

Flexible work arrangements

改善点

Long hours and heavy workload

Management issues and lack of direction

High stress during peak times

給与レンジ

41件のデータ

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analytics Solutions Associate

1件のレポート

$139,000

年収総額

基本給

$107,000

ストック

-

ボーナス

-

$139,000

$139,000

面接体験

5件の面接

難易度

3.0

/ 5

期間

14-28週間

内定率

40%

体験

ポジティブ 20%

普通 80%

ネガティブ 0%

面接プロセス

1

Application Review

2

HireVue Video Interview

3

Recruiter Screen

4

Superday/Panel Interview

5

Final Interview

6

Offer

よくある質問

Behavioral/STAR

Technical Knowledge

Culture Fit

Past Experience

Case Study