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JobsJPMorgan Chase

Senior Lead Software Engineer - Python / Java

JPMorgan Chase

Senior Lead Software Engineer - Python / Java

JPMorgan Chase

LONDON, LONDON, United Kingdom, GB

·

On-site

·

Full-time

·

2w ago

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

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 Python Engineer at JPMorgan Chase within the AM Research 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, particularly in cloud-based systems and AI-driven solutions.

Job responsibilities:

  • Develops secure and high-quality production code, and reviews and debugs code written by others, with a focus on cloud-based systems using AWS and Python.
  • Implements and optimizes RAG-based semantic search and LLM inference workflows using OpenAI and Claude models.
  • Drives decisions that influence the product design, application functionality, and technical operations and processes.
  • Serves as a function-wide subject matter expert in cloud deployment and AI technologies.
  • Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle.
  • Influences peers and project decision-makers to consider the use and application of leading-edge technologies.
  • Adds to the team culture of diversity, opportunity, inclusion, and respect.

Required qualifications, capabilities, and skills:

  • Formal training or certification on Java / Python concepts and proficient advanced experience.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability, particularly in cloud environments.
  • Advanced proficiency in Python programming.
  • Advanced knowledge of cloud-based systems, artificial intelligence, and machine learning, with considerable in-depth knowledge in implementing solutions using AWS.
  • Ability to tackle design and functionality problems independently with little to no oversight, demonstrating self-starter capabilities.
  • Practical cloud-native experience, specifically with AWS.
  • Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field.

Preferred qualifications, capabilities, and skills

  • Experience with RAG-based semantic search and LLM inference workflows using OpenAI and Claude models.
  • Proven track record of proposing solutions independently and owning execution end-to-end in an individual contributor role.

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About JPMorgan Chase

JPMorgan Chase

JPMorgan Chase is a multinational investment bank and financial services company that provides banking, investment, and asset management services globally. It is one of the largest banks in the United States by assets and market capitalization.

300,000+

Employees

New York City

Headquarters

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

47 data points

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

21 reports

$126,500

total / year

Base

$110,000

Stock

-

Bonus

-

$95,450

$155,250

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