Lead Software Engineer / Platform Engineer

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 JPMorganChase within the Corporate Sector - Employee Platforms team, 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. The Branch Technology engineering team builds software-defined platforms that manage and automate technology across the Retail Branch network. It is a small, focused team where engineers work across the stack, own their delivery end to end, and operate close to the architecture. The team moves fast, holds a high bar, and expects every engineer to bring their full capability to the work. As a Senior Lead Software Engineer, your focus will be the Software Defined Branch platform - contributing to the modernization of the C#, .NET, and PowerShell workflows that drive branch builds and Windows automation at scale. You will work alongside experienced engineers to re-shape those systems into a clean, maintainable, and extensible agentic platform, taking on complex problems and delivering with a level of craft the team can build on. You will be expected to bring AI tools into your daily workflow, engage with emerging agentic patterns on the CDAO Fusion Studio platform, and operate with the kind of autonomy and judgement that a lean, high-performing team depends on.

Requirements

Formal training or certification on software engineering concepts and 5+ years applied experience
Hands-on experience with AI-assisted development tools - VS Code, GitHub Copilot, Claude Code, or equivalent - and working knowledge of LLM integration or agentic tooling in a production context
Minimum 7 years of deep working knowledge of C#, .NET, and PowerShell in production environments
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Experience with Windows platform engineering and automation workflows at scale
Strong understanding of REST API design, relational database development, and system integration patterns
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
In-depth knowledge of the financial services industry and their IT systems
Ability to operate with autonomy, take technical ownership, and contribute at a high level within a small, senior team

Nice To Haves

Experience with front-end frameworks (React or equivalent) - the stack has a UI layer
Experience with event-driven architecture or messaging platforms
Familiarity with MCP (Model Context Protocol) or tools-first API design patterns
Experience in financial services or a comparable enterprise environment
Background in platform modernization or legacy system re-architecture

Responsibilities

Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
Develops secure and high-quality production code, and reviews and debugs code written by others
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
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.
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