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JPMorgan Chase
JPMorgan Chase

Global financial services firm

Lead Software Engineer - Java/React

职能前端
级别Lead级
地点GLASGOW, LANARKSHIRE, United Kingdom
方式现场办公
类型全职
发布2个月前
立即申请

必备技能

Java

React

GraphQL

Kafka

This is an exciting opportunity for you to join a talented team of engineers and make a global impact. As a Lead Software Engineer, you’ll help shape market-leading technology products that advance our business and deliver trusted solutions worldwide. You’ll collaborate with passionate professionals, solve complex problems, and grow your career in a supportive, innovative environment. We value your expertise, creativity, and commitment to teamwork.

As a Lead Software Engineer at JPMorgan Chase in Enterprise Observability Platforms, you will develop strategic software products critical to business advancement. You will lead an agile team, enhance and deliver secure, stable, and scalable technology solutions, and contribute across multiple technical areas. Your role will involve driving innovation, applying software engineering best practices, and fostering a culture of diversity, equity, inclusion, and respect. Together, we’ll deliver solutions that support the firm’s business objectives.

Job Responsibilities

  • Execute creative software solutions across design, development, and advanced technical troubleshooting, think beyond routine approaches to build solutions and break down complex technical problems.
  • Lead the migration from a legacy monolith to a modern, containerized microservices architecture (React/Java/Spring Boot), including decomposition strategy, domain modeling, and data migration planning.
  • Re‑architect existing infrastructure to achieve high scalability, reliability, and availability (multi‑AZ/region patterns, autoscaling, HA/DR).
  • Deliver full‑stack features end‑to‑end, build backend services and APIs (REST/GraphQL) in Java/Spring Boot and contribute to operational UIs/console experiences as needed.
  • Design and implement event‑driven systems and streaming‑based alerting workflows (e.g., Kafka), including sound topic/schema design and resilient consumer strategies.
  • Build and evolve secure, high‑quality production services; review, debug, and improve code written by others to raise engineering standards.
  • Drive performance, resiliency, and scalability improvements for firmwide alerting and event routing; instrument SLOs/SLIs and optimize p99 latency and throughput. Collaborate cross‑LOB with product, application teams, SRE/operations, and controls to ensure reliable adoption and effective incident response.
  • Explore and evaluate AI for Ops approaches with partners across SRE and observability. Drive POCs and data‑driven adoption where appropriate.
  • Lead evaluation and architecture discussions with internal teams (and vendors when applicable) to assess designs, technical credentials, and fit within enterprise architectures. Contribute to communities of practice to promote awareness and adoption of modern engineering and observability practices.
  • Add to a team culture of diversity, opportunity, inclusion, and respect.

Required qualifications, capabilities, and skills

  • Significant professional software engineering experience, including leading cross‑team initiatives (Lead level).
  • Hands‑on experience delivering system design, application development, testing, and operational stability for distributed systems.
  • Advanced proficiency in Java and building microservices with Spring Boot, strong system design expertise.
  • Full‑stack engineering mindset with the ability to work across backend and UI layers as needed (backend‑heavy).
  • Proficiency in automation and continuous delivery methods; experience implementing CI/CD pipelines.
  • Proficient across the Software Development Life Cycle (SDLC): requirements, design, coding, testing, deployment, and support.
  • Advanced understanding of agile methodologies and practices, including CI/CD, application resiliency, and security .
  • Cloud‑native experience deploying containerized microservices in cloud.
  • Working knowledge of relational databases (Oracle).

Preferred qualifications, capabilities, and skills

  • Proficiency with Kubernetes (e.g., EKS) for container orchestration and operations.
  • Proficiency with event‑streaming platforms (e.g., Kafka) and event‑driven architectural patterns.
  • Experience designing and operating distributed systems at scale (microservices, multi‑region failover).
  • Experience building modern frontend applications with React and TypeScript for operational consoles/UX.
  • Expertise with AWS services aligned to containerized workloads and streaming. Familiarity with CockroachDB is a plus.
  • Infrastructure‑as‑Code (e.g., Terraform, Helm) and configuration management. Observability tooling familiarity (e.g., Prometheus/Grafana, Open Telemetry, Splunk/ELK) and defining SLOs/SLIs.
  • Experience mentoring engineers, conducting design reviews, and establishing engineering standards/best practices. Effective communication and stakeholder management across product, operations, and controls.

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关于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+

员工数

New York City

总部位置

$500B

企业估值

评价

10条评价

3.8

10条评价

工作生活平衡

3.5

薪酬

4.0

企业文化

3.8

职业发展

3.2

管理层

2.8

68%

推荐率

优点

Good benefits and compensation

Supportive colleagues and environment

Flexible work arrangements

缺点

Long hours and heavy workload

Management issues and lack of direction

High stress and expectations

薪资范围

44个数据点

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analytics Solutions Associate

1份报告

$139,000

年薪总额

基本工资

$107,000

股票

-

奖金

-

$139,000

$139,000

面试评价

4条评价

难度

3.0

/ 5

时长

14-28周

录用率

50%

体验

正面 25%

中性 75%

负面 0%

面试流程

1

Application Review

2

HR Screen

3

Hiring Manager Interview

4

In-person/Final Interview

5

Offer

常见问题

Behavioral/STAR

Past Experience

Culture Fit

Financial Knowledge

Case Study