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JPMorgan Chase
JPMorgan Chase

Global financial services firm

Lead Software Engineer, AI Cloud Infrastructure

职能DevOps
级别Lead级
地点Seattle, WA, United States
方式现场办公
类型全职
发布3个月前
立即申请

必备技能

Python

AWS

Go

Terraform

GCP

Azure

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 JPMorgan Chase within the Chief Data and Analytics Office, 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.

Job responsibilities

  • Architect solutions to enhance the reliability and scalability of AI/ML platforms and applications to accommodate fast growing demands.

  • Create the tooling and services needed to safely deploy and operate ML Models.

  • Build monitoring and observability tools to track model performance, data quality, and system health

  • Reduce operational toil by automating repetitive tasks and building self-healing systems and remediation workflows.

  • Build strong cross-functional relationships that foster engagements across the organization and deliver solutions to user problems.

  • Participates in on-call rotations and debug and solve issues in a production environment.

  • Take full ownership of problems, develop solutions, and acquire new knowledge to complete the task.

  • Mentor and guide junior engineers.

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 proficiency in one or more programming languages (Python, Go).

  • Proficiency in automation and continuous delivery methods.

  • Proficient in all aspects of the Software Development Life Cycle.

  • Hands-on experience with Google Cloud platform (GCP).

  • Strong proficiency with IaC tools (Terraform) and Google Cloud Client Libraries.

  • Systematic problem-solving and troubleshooting skills in a complex system.

  • Excellent communication skills and ability to represent and present business and technical concepts to stakeholders.

  • Self-managed, self-motivated with strong sense of ownership, urgency, and drive

Preferred qualifications, capabilities, and skills

  • Prior experience in Google Vertex AI, AWS Bedrock, Azure OpenAI.

  • Prior experience working in GPU scheduling, Model deployment or ML training workloads.

  • Prior experience developing GenAI Apps, AI Agents, Vector Search, and RAG patterns.

  • Extensive experience implementing advanced observability using tools like Open Telemetry, Dynatrace, Grafana, and/or cloud-native services.

  • Multi cloud experience such as (AWS/Azure) is a plus

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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