Lead Software Engineer - Java/Python, AWS & AI/ML

JPMorgan Chase & Co.•Plano, TX

About The Position

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking - Home Lending, 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.

Requirements

Formal training or certification on software engineering concepts and 5+ years applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced in one or more programming language(s)
Proven experience with AWS, GraphQL, REST APIs, Python, and Java.
Strong background in AI/ML, including RAGs, vector databases, LLMs, and agentic workflow design.
Hands-on coding and solution delivery in complex environments.
Expertise in building observability solutions: distributed tracing, logging, metrics, time series DBs, dashboarding, alerting, and monitoring.
Experience developing and deploying AI Ops models.
Excellent problem-solving, communication, and leadership skills.
Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field

Nice To Haves

Certification in AWS – Solutions Architect
Creating Release Management Solutions
Creating Incident Management Solutions

Responsibilities

Lead and deliver innovative technology solutions within the Home Lending organization.
Design, develop, and deploy applications using modern tech stacks (AWS, GraphQL, REST, Python, Java).
Build and integrate AI/ML solutions, including Retrieval-Augmented Generation (RAG), vector databases, and Large Language Models (LLMs) for agentic workflows.
Provide hands-on coding expertise and lead initiatives.
Develop observability frameworks using distributed tracing, logs, metrics, time series databases, and dashboards.
Implement robust alerting and monitoring systems to ensure platform reliability.
Design and deploy AI Ops models for intelligent operations and automation.
Adds to the team culture of diversity, opportunity, inclusion, and respect