Job Responsibilities
- Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
- 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
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience.
- Hands-on practical experience in Python, SQL, Databricks, Knowledge Graphs in Production
- Advanced in one or more programming language(s) like Python
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
- Highly proficient in coding in one or more languages such as Python, SQL, Java and R programming languages Experience with one or more platform tech stacks such as AWS, Docker, Kubernetes, Data bricks and CI/CD pipelines.
- Solid understanding of using ML techniques specially in Natural Language Processing (NLP), Knowledge Graph and Large Language Models (LLMs)
- Proficient in all aspects of the SDLC and ADLC
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Proficiency in optimizing and tuning AI models to ensure efficient, scalable solutions, with experience in building and deploying ML models on cloud platforms such as AWS and using tools like Sagemaker and EKS
- Knowledge of the financial services industry and their IT systems
- Cloud native experience -AWS
- Knowledge of data engineering practices to support AI model training and deployment, along with a strong understanding of machine learning algorithms and techniques—including supervised, unsupervised, and reinforcement learning—and hands-on experience with libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras
Skills Required
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Hands-on practical experience in Python, SQL, Databricks, and Knowledge Graphs in production
- Advanced proficiency in one or more programming languages such as Python
- Demonstrated experience leading enterprise-authorized AI-assisted software development tools and validating AI outputs
- Strong understanding of responsible AI usage, data sensitivity, secure handling, resiliency, and coaching senior engineers on compliant patterns
- Proficiency coding in Python, SQL, Java and R and experience with platform tech stacks such as AWS, Docker, Kubernetes, Databricks, and CI/CD pipelines
- Solid understanding of ML techniques, especially NLP, Knowledge Graphs, and Large Language Models
- Proficient in all aspects of the SDLC and ADLC
- Advanced understanding of agile methodologies including CI/CD, application resiliency, and security
- Experience optimizing/tuning AI models and deploying ML models on cloud platforms such as AWS using tools like SageMaker and EKS
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical, dental, vision, and mental health coverage are comprehensive, with on-site clinics, preventive care, and specialized supports such as maternity nurse guidance and fertility treatments. Wellness activities can help offset copays and out-of-pocket costs, reinforcing the perceived strength of health benefits.
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Retirement Support — A 401(k) with dollar-for-dollar matching and additional automatic pay credits reflect strong employer-backed retirement savings. An employee stock purchase plan and related financial programs further bolster long-term financial support.
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Leave & Time Off Breadth — Paid time off, sick time, holidays, and generous parental leave are provided alongside family medical leave and adoption/fertility assistance. Additional programs like caregiver support and volunteer time off expand the breadth of time-away options.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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