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Sr. Lead Software Engineer - Java, Spring, API, AWS

JPMorgan Chase

Sr. Lead Software Engineer - Java, Spring, API, AWS

JPMorgan Chase

Wilmington, DE, United States, US

·

On-site

·

Full-time

·

2mo ago

Required skills

Java

React

AWS

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
  • Java, Spring, API, AWS at JPMorgan Chase within our Corporate sector's Global Finance Technology team, you will play a pivotal role in an agile team focused on developing secure, stable, and scalable technology products. You will leverage your technical expertise to solve complex challenges across various technologies and applications, significantly impacting the business. Your responsibilities include contributing production-quality code, writing tests, performing code reviews, and engaging in pair programming. You will design and deliver secure microservices and web applications using Java/Spring Boot and React, while also handling deep debugging and performance tuning. You will oversee the end-to-end build-and-run process, ensuring high-quality service delivery. As a technical leader, you will set engineering standards and provide guidance on architecture, code quality, and operational excellence. You will act as a subject matter expert in microservices, CI/CD, and performance engineering, while championing SDLC practices. Additionally, you will evaluate and introduce technologies to enhance reliability, scalability, and cost efficiency. Your role will also involve embedding non-functional requirements into designs and fostering an inclusive team culture through mentorship and continuous improvement.

Job responsibilities

  • Lead by example: contribute production‑quality code daily, write tests, perform code reviews, and pair program.
  • Design and deliver secure, high‑quality microservices and web applications with Java/Spring Boot and React; own deep debugging, root‑cause analysis, and performance tuning for high-availability services.
  • Own end‑to‑end build‑and‑run: design, implement, test, deploy, and operate services (“you build it, you run it”).
  • Provide technical leadership across teams; set engineering standards and coach on architecture, code quality, security, and operational excellence.
  • Act as SME for microservices, CI/CD, observability, performance engineering, and data modeling.
  • Champion SDLC practices: test automation, CI/CD, security‑by‑default, quality gates, and disciplined change management.
  • Evaluate and introduce technologies that improve reliability, scalability, cost efficiency, and auditability.
  • Embed non‑functional requirements (security, scalability, reliability, observability, cost) into designs; implement logging, metrics, tracing, SLOs, error budgets, alerting, and runbooks.
  • Foster an inclusive team culture; mentor engineers and drive continuous improvement and craftsmanship.

Required qualifications, capabilities, and skills

  • Formal training or certification in software engineering and 5+ years of applied experience.
  • Advanced proficiency in Java and Spring Boot; strong fundamentals, design patterns, and secure coding.
  • Full‑stack delivery with React (component/state management) and secure RESTful API design.
  • Hands‑on AWS experience (EC2, ECS, S3, Lambda, RDS, IAM), including containerized workloads, networking, and secrets management.
  • Microservices design, deployment, and operations.
  • CI/CD pipelines (Jenkins/GitHub Actions), automated testing (unit/integration/contract), and enforcing quality gates.
  • Relational and NoSQL databases: schema design, performance tuning, and secure data access.
  • Monitoring and logging with Data Dog, Dynatrace, and/or Splunk.
  • Reliability and performance engineering: concurrency, thread management, caching, and resiliency patterns (circuit breakers, retries, backoff), with cost awareness.
  • Proven track record shipping and operating production systems; comfortable troubleshooting in Kubernetes, CI/CD, and cloud environments.
  • Hands‑on use of AI coding assistants to accelerate delivery (e.g., GitHub Copilot): prompt design, code/test generation, refactoring, and documentation synthesis; ability to validate outputs for correctness, security, performance, and licensing compliance. Use subject to company-approved tools and policies.
    Preferred qualifications, capabilities, and skills- Understanding of regulatory finance/external reporting (workflows, reconciliations, controls).
  • Cloud certifications; proven cloud‑native delivery on AWS.
  • Experience with large‑scale distributed systems, event‑driven architectures, and messaging/streaming patterns.
  • Observability/SRE depth: telemetry pipelines, alerting strategies, incident response, post‑mortems, and continuous improvement.

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About JPMorgan Chase

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+

Employees

New York City

Headquarters

$500B

Valuation

Reviews

3.8

10 reviews

Work-life balance

3.2

Compensation

4.1

Culture

3.8

Career

3.0

Management

2.5

65%

Recommend to a friend

Pros

Good benefits and compensation

Supportive and collaborative environment

Flexible work arrangements

Cons

Long hours and heavy workload

Management issues and lack of direction

High stress during peak times

Salary Ranges

41 data points

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analytics Solutions Associate

1 reports

$139,000

total per year

Base

$107,000

Stock

-

Bonus

-

$139,000

$139,000

Interview experience

5 interviews

Difficulty

3.0

/ 5

Duration

14-28 weeks

Offer rate

40%

Experience

Positive 20%

Neutral 80%

Negative 0%

Interview process

1

Application Review

2

HireVue Video Interview

3

Recruiter Screen

4

Superday/Panel Interview

5

Final Interview

6

Offer

Common questions

Behavioral/STAR

Technical Knowledge

Culture Fit

Past Experience

Case Study