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Lead Software Engineer ​/ Platform Engineer

Job in Raleigh, Wake County, North Carolina, 27601, USA
Listing for: 慨正橡扯
Full Time position
Listed on 2026-08-08
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), DevOps, Software Engineer, Backend Developer
Salary/Wage Range or Industry Benchmark: 140000 - 210000 USD Yearly USD 140000.00 210000.00 YEAR
Job Description & How to Apply Below

JOB DESCRIPTION

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 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 firmu
2019s 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 Power Shell workflows that drive branch builds and Windows automation  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.

Job 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
Required qualifications, capabilities, and skills
  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on experience with AI-assisted development tools - VS Code, Git Hub 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 Power Shell 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,…
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