Jobs

Java Lead Software Engineer - Morgan Money (AWM)
Columbus, OH, United States, US
·
On-site
·
Full-time
·
1mo ago
Required skills
Python
Java
Kafka
Machine Learning
Morgan Money has revolutionized liquidity trading across the firm serving our corporate clients in all regions to have next generation trading capabilities at their fingertips.
As a Lead Software Engineer at JPMorgan Chase within the Asset and Wealth Management (AWM), we are increasing our presence in Columbus and this is an opportunity to play a part in one of the most exciting technology agendas in the firm right now, as we look to grow the solution further by several flag-ship technology innovation streams. This is an opportunity to join the engineering team responsible for the platform supporting:
- $31Bn average daily gross trading volume
- In excess of 6700 active clients
- Over $400Bn Assets under management
Job responsibilities
- Confidently collaborates directly with Investment Teams, Traders, and Portfolio Managers, effectively bridging communication without relying on business analysts or Project Managers.
- Thrives in a fast-paced environment, contributing to one of Asset Management’s most high-profile platforms.
- Operates as part of an agile team, regularly deploying software updates to production and adjusting to the dynamic needs and scale of the business.
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Serves as a function-wide subject matter expert in one or more areas of focus
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Develops secure and high-quality production code, and reviews and debugs code written by others.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Have excellent programming experience in Core Java
- Implement TDD and BDD techniques, with a focus on leveraging mocking frameworks for effective testing
- Demonstrate an understanding of IoC frameworks in Java, such as native Spring or Guice
- Understand next generation messaging and streaming technologies such as Kafka, IBM MQ, Solace or Ignite
- Strong grasp of engineering principles, including CI/CD, application resiliency, and security.
- Demonstrated knowledge of software applications and technical processes within a technical discipline (cloud, artificial intelligence, machine learning, etc.)
- Overall knowledge of the Software Development Life Cycle
Preferred qualifications, capabilities, and skills
- Have exposure to working with trading, FIX engines or related technologies.
- Experience in smart contracts, Ethereum and digital wallets
- Exposure to cloud technologies and certification
- Python skills are highly desirable
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About JPMorgan Chase

JPMorgan Chase
PublicJPMorgan 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
4.2
10 reviews
Work-life balance
4.2
Compensation
4.3
Culture
4.5
Career
4.4
Management
4.1
75%
Recommend to a friend
Pros
Good pay and benefits
Work-life balance
Career advancement opportunities
Cons
Heavy workload at times
Career advancement takes time
Pay could be better in some roles
Salary Ranges
55 data points
Mid/L4
Senior/L5
Mid/L4 · Applied AI ML Associate
2 reports
$188,500
total per year
Base
$145,000
Stock
-
Bonus
-
$182,000
$195,000
Interview experience
4 interviews
Difficulty
2.8
/ 5
Duration
14-28 weeks
Interview process
1
Application Review
2
HireVue Video Interview
3
Technical/Behavioral Assessment
4
Final Interview Round
5
Offer Decision
Common questions
Behavioral/STAR
Technical Knowledge
Past Experience
Culture Fit
Case Study
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