Lead Software Engineer - Python/AWS/Kafka
Company: JPMorganChase
Location: Columbus
Posted on: April 1, 2026
|
|
|
Job Description:
Description 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
Cybersecurity Technology and Controls 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. 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. We are seeking a highly skilled Lead
Software Engineer with expertise in deploying, monitoring, and
managing machine learning models in production environments. This
role involves working with cutting-edge technologies to ensure
scalable, reliable, and efficient AI solutions. The ideal candidate
will be adept at building robust infrastructure and processes to
support the seamless operation of machine learning models. In this
role, you will be responsible for automating model deployment,
optimizing infrastructure, and ensuring the continuous performance
of AI systems. Your ability to collaborate with cross-functional
teams and address operational challenges will be crucial to driving
innovation and delivering impactful AI solutions. Job
responsibilities Collaborate with cross-functional teams, including
data scientists and software engineers, to understand model
requirements and integrate them into applications. Develop and
implement strategies for deploying machine learning models into
production, ensuring scalability, reliability, and efficiency.
Design and maintain continuous integration and continuous
deployment (CI/CD) pipelines to automate the testing, deployment,
and updating of machine learning models. Manage and optimize the
infrastructure required for running machine learning models,
including cloud services, containerization (e.g., Docker), and
orchestration tools (e.g., Kubernetes). Implement monitoring and
logging solutions to track model performance, detect anomalies, and
ensure models are operating as expected in production. Maintain
version control for models and data, ensuring traceability and
compliance with governance policies and ensure that deployed models
adhere to security best practices and comply with relevant
regulations and standards. Executes creative software solutions,
design, development, and technical troubleshooting with ability to
think beyond routine or conventional approaches to build solutions
or break down technical problems Develops secure high-quality
production code, and reviews and debugs code written by others
Identifies opportunities to eliminate or automate remediation of
recurring issues to improve overall operational stability of
software applications and systems Leads communities of practice
across Software Engineering to drive awareness and use of new and
leading-edge technologies Required qualifications, capabilities,
and skills Obtain 6 years of applied experience and/or
certification in cybersecurity/engineering concepts, Bachelor's
degree in Computer Science, Engineering, or a related field, with
relevant experience in ML Ops or related roles. Advanced Python
Programming Skills including Pandas, Numpy and Scikit- Learn
Proficiency in building and maintaining CI/CD pipelines for machine
learning workflows. Proficient in all aspects of the Software
Development Life Cycle Advanced understanding of agile
methodologies such as CI/CD, Application Resiliency, and Security
Expertise in cloud platforms (e.g., AWS, Google Cloud, Azure) and
containerization technologies (e.g., Docker, Kubernetes).
Familiarity with monitoring and logging tools (e.g., Prometheus,
Grafana, ELK Stack). Excellent problem-solving skills and attention
to detail and Strong communication skills to collaborate
effectively with cross-functional teams. Hands-on practical
experience delivering system design, application development,
testing, and operational stability Preferred qualifications,
capabilities, and skills Proven experience in deploying and
managing large-scale machine learning models in production
environments. Demonstrated proficiency in software applications and
technical processes within a technical discipline (e.g., cloud,
artificial intelligence, machine learning, mobile, etc.) Ability to
monitor ML models in production, addressing model performance and
data quality issues effectively. Working knowledge of security best
practices and compliance standards for Machine Learning systems.
Experience with infrastructure optimization techniques to enhance
performance and efficiency. Development of REST APIs using
frameworks such as Flask or FastAPI for seamless integration into
business solutions. Familiarity with creating and utilizing
synthetic datasets to improve model training and evaluation.
CTC
Keywords: JPMorganChase, Dayton , Lead Software Engineer - Python/AWS/Kafka, IT / Software / Systems , Columbus, Ohio
