Lead Software Engineer - Full Stack/AI Engineering Focus

JPMorganChase•Plano, TX

About The Position

As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank - Digital & Platform Services team, you will contribute to an agile team that builds and delivers secure, stable, scalable technology products. You will provide technical solutions across multiple areas and business functions in support of the firm’s objectives, with a full-stack and AI engineering focus. You will lead end-to-end delivery of platform capabilities and application features, from requirements and design through development, testing, deployment, production support, and continuous improvement. The role includes developing cloud-native microservices and APIs, modern React and TypeScript interfaces, and event-driven systems, while guiding architecture and engineering practices. You will also advance operational reliability and use approved AI tools and agentic solutions to improve software delivery and engineering workflows, following governance, security, and validation practices.

Requirements

Formal training or certification in software engineering concepts and 5+ years of applied experience.
10+ years of hands-on software engineering experience building and supporting enterprise-scale applications.
Strong expertise designing and developing backend services using Java, Spring Boot, distributed systems, and microservice architectures.
Demonstrated experience leading effective use of approved AI-assisted software development tools, with the ability to set expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption.
Hands-on experience building and consuming REST and/or GraphQL APIs.
Strong experience with relational databases, SQL optimization, and data access patterns.
Experience implementing event-driven and streaming architectures using Kafka or equivalent messaging platforms.
Experience building modern frontend applications using React and TypeScript.
Experience with observability and operational tooling such as Splunk, Grafana, Kibana, ELK, OpenTelemetry, Postman, or equivalent platforms.
Proficiency with modern engineering tooling including Git, GitHub, Maven, Jenkins, SonarQube, IntelliJ IDEA, VS Code, Jira, and Confluence.

Nice To Haves

Working knowledge of Python, including its use for automation, data processing, or AI-enabled solutions.
Experience designing and deploying AI agents and agentic workflows for software engineering, operations, or business process automation.
Understanding of Model Context Protocol (MCP) and modern AI integration patterns.
Knowledge of prompt engineering techniques, AI workflow design, and human-in-the-loop systems.
Experience creating agentic automations to improve SDLC productivity, testing, code reviews, documentation generation, CI/CD operations, or incident management.
Demonstrated ability to establish governance, validation, and quality controls for AI-generated code and solutions.
Working knowledge of Elasticsearch or OpenSearch, including index design, query optimization, and operational management.

Responsibilities

Design, develop, and deliver scalable, secure, and resilient full-stack solutions using Java, Spring Boot, React, and TypeScript.
Own end-to-end delivery of platform capabilities and application features, including requirements analysis, solution design, development, testing, deployment, production support, and continuous improvement.
Lead the design and development of cloud-native, containerized microservices and platform services, emphasizing domain-driven design, API-first development, performance, security, maintainability, and operational excellence.
Drive technical architecture and design decisions, collaborating with product managers, architects, and engineering teams to align with enterprise standards and long-term technology strategies.
Build and enhance backend services and REST or GraphQL APIs, integrating with enterprise platforms, relational databases, search technologies, and distributed data systems.
Develop operational and administrative user interfaces using React and TypeScript.
Design and implement Kafka-based event-driven and streaming architectures, including event modeling, schema governance, topic strategy, and resilient producer-consumer patterns.
Champion engineering excellence through code reviews, troubleshooting, refactoring, performance tuning, and mentoring.
Improve application reliability, observability, and operational stability through automation, monitoring, distributed tracing, incident management, root cause analysis, and technical-debt reduction.
Use enterprise-approved AI-assisted engineering tools to accelerate delivery, improve productivity, automate repetitive tasks, and enhance code quality while following governance, security, and validation practices.
Evaluate, design, and implement AI-powered and agentic solutions for software development, operational workflows, system support, and engineering processes, with measurable business and productivity outcomes.