JPMorgan Chase
From JPMorgan Chase's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
You will create platform capabilities that help teams move from ideas to production with confidence.
Join a team where your engineering work accelerates how machine learning is built, governed, and delivered across JPMorganChase. You will create platform capabilities that help teams move from ideas to production with confidence. If you enjoy building scalable systems and improving developer experience, this role offers meaningful impact and growth.
As a Software Engineer III at JPMorganChase within the Corporate Artificial Intelligence and Machine Learning Data Platforms team, you will build and enhance products that support the end-to-end machine learning lifecycle, including model operations, data development (including processing and data annotation), and governance tooling. You will collaborate with engineers, system architects, product managers, data scientists, and research partners to deliver reliable, secure, and user-friendly platform services.
Job responsibilities
Build and enhance platform services for model registries, feature registries, promotion policies, and governance workflows
Design and deliver capabilities for data preparation, annotation workflows, lineage, and audit trails
Develop cloud-native services and application programming interfaces that scale across development and production environments
Implement large language model-powered features (prompt design, agent workflows, tool integration, retrieval) with strong controls and evaluation practices
Produce and maintain architecture and design artifacts; ensure solutions meet performance, resiliency, and security expectations
Use approved AI-assisted development tools responsibly, validating outputs through code review, testing, and secure coding practices
Partner with product and engineering stakeholders to prioritize roadmap items and improve platform usability
Analyze operational metrics and user feedback to improve reliability, usability, and platform adoption
Identify and remediate issues in systems and data; improve code quality, observability, and maintainability
Required qualifications, capabilities and skills
Formal training or certification on software engineering concepts and 3+ years applied experience
Experience building and delivering backend or platform services using modern architecture patterns, including microservices, reactive architectures, or event-driven architectures
Experience developing and deploying large language model-powered solutions using prompt design, agent workflows, tool integration, and retrieval techniques
Proficiency in at least two modern languages or frameworks such as Python, Java, JavaScript, React, or Node.js
Experience building and consuming RESTful application programming interfaces, including performance tuning in large-scale applications
Experience with cloud platforms and containerization or orchestration tools such as Docker and Kubernetes
Experience with relational and non-relational databases such as PostgreSQL, MongoDB, Redis, Elasticsearch, or Cassandra
Experience with engineering practices including refactoring, design patterns, automated testing, continuous integration, continuous delivery, and application security
Hands-on experience using approved AI-assisted software development tools, with the ability to validate and refine outputs for correctness, performance, and security
Proficiency in Go or Terraform for automation, tooling development, or platform service implementation
Working knowledge of machine learning frameworks such as PyTorch, TensorFlow, Hugging Face, or scikit-learn for model integration and operationalization
Exposure to multi-cloud or hybrid cloud architectures and platform portability strategies
Experience building governance controls for model lifecycle management, including approvals, policy enforcement, and auditability
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