We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As an AI ML engineer at JPMorgan Chase within the Commercial & Investment Bank's Global Banking team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading AI 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

Deliver AI/ML projects through our ML development life cycle using Agile methodology. Help transform business requirements into AI/ML specifications, define milestones, and ensure timely delivery.Executes solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problemsCreates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systemsProduces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code developmentGathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systemsProactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architectureContributes to software engineering communities of practice and events that explore new and emerging technologies

 

Required Qualifications, Capabilities, and Skills

Formal training or certification on Software Engineering concepts and 3+ years applied experienceProficient in Python programming languageHands-on experience developing production AI/ML solutionsFamiliarity with agentic workflows and relevant frameworks, such as LangChain, LangGraph, CrewAI, Auto-GPT, etc.Familiarity with Large Language Models, RAG, Vector Store, and MCPDemonstrated understanding of machine learning frameworks such as TensorFlow, Keras, PyTorch, Scikit-learn, NumPy, etc.Familiarity with AWS Cloud services such as SageMaker, EMR, Glue, etc.Solid understanding of the Software Development Life Cycle, CI/CD, application resiliency, and security

Preferred Qualifications, Capabilities, and Skills

Experience with relational and/or NoSQL databasesExperience with Apache Spark and DatabricksExperience with Terraform