
Global financial services firm
Lead Software Engineer – Python, AIML, Cloud
Required skills
Python
AWS
Docker
Kubernetes
Terraform
Kafka
Machine Learning
J.P.Morgan Chase is seeking a Lead Software Engineer with expertise in AWS and Python, and a passion for Machine Learning, to help engineer and deploy innovative ML solutions into production. You will collaborate with the Applied AI/ML group and technology teams across the firm, contributing to both new and ongoing projects.
In this role, you will work alongside Data Scientists to build cloud-based frameworks for hosting machine learning models, providing software engineering expertise throughout the model development lifecycle. You will leverage both internal and external cloud platforms, utilizing proprietary and open-source tools to ensure models meet SDLC standards, are production-ready, and can be deployed efficiently. The position requires close interaction with platform developers, engineering communities, and the integration of existing and new technologies.
Job Responsibilities
- Develop and maintain high-quality, secure applications using Python and AWS
- Create architecture and design deliverables, lead design and architecture reviews, promote best practice
- Integrate AIML solutions into complex, domain-specific operations processing systems
- Lead code reviews, design discussions, and agile planning sessions
- Collaborate with SRE and production monitoring teams to ensure system reliability and performance
- Contribute to software engineering communities of practice and technology events
- Embrace continuous learning, creative problem-solving, and a can-do attitude
Required Qualifications, Capabilities, and Skills
- Bachelor’s degree or higher in Computer Science, Engineering, or a related field, or equivalent formal training/certification
- Proven hands-on experience in Python application development
- Proven hands-on experience developing, debugging and maintaining production applications
- Solid understanding of software development best practices, including version control, testing, and CI/CD
- Strong problem-solving, communication, and collaboration skills, with the ability to convey design choices and communicate effectively with stakeholders
- Experience working on AIML systems and/or prior experience collaborating with data scientists
- Track record of designing, building, and delivering maintainable, extensible applications into production environments
Preferred Qualifications, Capabilities, and Skills
- Experience with Cloud services, Infrastructure as Code (IaC, Terraform) and containerized application development
- Familiarity with data storage systems (e.g., Postgres, Open Search) and AWS services such as S3, Sage Maker, and Bedrock
- Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps, Large Language Model Operations (LLMOps), Event Driven Systems.
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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
10 reviews
3.8
10 reviews
Work-life balance
3.5
Compensation
4.0
Culture
3.8
Career
3.2
Management
2.8
68%
Recommend to a friend
Pros
Good benefits and compensation
Supportive colleagues and environment
Flexible work arrangements
Cons
Long hours and heavy workload
Management issues and lack of direction
High stress and expectations
Salary Ranges
44 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
4 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer rate
50%
Experience
Positive 25%
Neutral 75%
Negative 0%
Interview process
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
In-person/Final Interview
5
Offer
Common questions
Behavioral/STAR
Past Experience
Culture Fit
Financial Knowledge
Case Study
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