As a Software Engineer III at JPMorganChase within the Commercial & Investment Bank - Data Analytics 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.

In this role, you will work alongside Data Scientists to build cloud-based frameworks for hosting machine learning models, providing software engineering expertise throughout the model development lifecycle. You will leverage both internal and external cloud platforms, utilizing proprietary and open-source tools to ensure models meet SDLC standards, are production-ready, and can be deployed efficiently. The position requires close interaction with platform developers, engineering communities, and the integration of existing and new technologies and a passion for Machine Learning, to help engineer and deploy innovative ML solutions into production. You will collaborate with the Applied AI/ML group and technology teams across the firm, contributing to both new and ongoing projects. 

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
• Develop and maintain high-quality, secure applications using Python and AWS 
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
• Integrate AIML solutions into complex, domain-specific operations processing systems 
• Contribute to software engineering communities of practice and technology events 
• Embrace continuous learning, creative problem-solving, and a can-do attitude 

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years applied experience 
• Hands-on practical experience in system design, application development, testing, and operational stability
• Proven hands-on experience in Python application development 
• 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.
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• Participate in code reviews, design discussions, and agile planning sessions 
• Collaborate with SRE and production monitoring teams to ensure system reliability and performance 
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Strong problem-solving, communication, and collaboration skills, with the ability to convey design choices and communicate effectively with stakeholders
• Familiarity with Machine Learning Operations (MLOps) 
   

Preferred qualifications, capabilities, and skills

• Experience with Cloud services, Infrastructure as Code (IaC) and containerized application development 
• Familiarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock 
• Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and Large Language Model Operations (LLMOps) 
• Experience working on AIML systems and/or prior experience collaborating with data scientists