Join our team as a Full Stack Software Engineer and play a pivotal role in shaping the future of Machine Learning and AI solutions within the Consumer & Community Banking sector at JPMorgan Chase.

As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

 

Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Develops secure high-quality production code, and reviews and debugs code written by others Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Adds to team culture of diversity, equity, inclusion, and respect

 

 

Required qualifications, capabilities, and skills

 

Formal training or certification on software engineering concepts and 5+ years applied experience Good experience of various machine learning algorithms, including supervised and unsupervised learning, neural networks and reinforcement learning Solid experience with Python, SQL, CI/CD pipeline, Github, AWS or Azure or GCP required End-to-end working knowledge on how a machine learning product is built Familiarity with MLOPS and components in MLOPS ecosystem Hands-on practical experience delivering system design, application development, testing, and operational stability Advanced in one or more programming language(s) Proficiency in automation and continuous delivery methods Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Practical cloud native experience

Preferred qualifications, capabilities, and skills

In-depth knowledge of the financial services industry and their IT systems Practical AWS or Azure cloud native experiences Experience with deploying applications using Docker, Kubernetes Experience in data streaming tools such as Kafka Experience with Generative AI and LLM’s