The role
From JPMorgan Chase's own posting.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.
As a Software Engineer III at JPMorgan Chase within Corporate AIML Data Platforms and Chief Data & Analytics (CDAO) team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
Develops and deploys AI/ML models and data pipelines for enterprise applications
Creates secure and high-quality production code for machine learning inference and training systems
Produces architecture and design artifacts for AI-powered applications while ensuring scalability and performance
Gathers, analyzes, and transforms large datasets to support AI/ML model development and evaluation
Implements natural language processing, generative AI, and other ML technologies in production systems
Collaborates with data scientists to productionize machine learning models and integrate with backend services
Contributes to AI/ML communities of practice through demos, tech talks, and knowledge sharing
Required qualifications, capabilities, and skills
Formal training or certification in software engineering and 3+ years applied experience
Hands-on experience with AI/ML model development, training, and deployment
Proficient in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn)
Proficient in Java for both client-side and server-side application development
Proficient in HTML, CSS, and modern front-end web development practices
Experience with data pipelines and processing frameworks (Spark, Pandas, NumPy)
Solid understanding of CI/CD, MLOps practices, and model versioning
Demonstrated knowledge of cloud platforms (AWS, Azure, GCP) and containerization
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Preferred qualifications, capabilities, and skills
Experience with generative AI and large language models (LLMs)
Familiarity with vector databases and RAG architectures
Experience with containerization (Docker, Kubernetes) and cloud-native deployments
Knowledge of NLP techniques and transformer architectures