Top Logistics Software Engineer Jobs in New York City, NY

As a Senior/Staff Software Engineer at CoPallet, you will build and maintain infrastructure for AI models, design scalable systems, and collaborate cross-functionally to deliver impactful solutions for logistics.

Lead the design, support, and implementation of warehouse management systems. Collaborate with cross-functional teams and troubleshoot technical issues to ensure system performance and business success.

The Principal Software Engineer will lead backend architecture, focusing on infrastructure, security, and developer experience. Responsibilities include designing scalable systems, mentoring engineers, and collaborating across teams to optimize productivity while ensuring security compliance.

The Senior Software Engineer will design and build Foley's Dash SaaS platform, focusing on backend development with collaboration across the stack, ensuring high-quality software delivery, and contributing to architectural modernization efforts.

The Director of Software Engineering leads technology and AI strategy, overseeing enterprise platforms, data infrastructures, and engineering talent development.

Design and build product features for a SaaS platform, lead technical projects, mentor engineers, and ensure high-quality code and user experience.

Mudflap seeks software engineers to build and scale their payments platform using Ruby on Rails, collaborating cross-functionally and owning features end-to-end.

Lead software engineering team, oversee AI-first transformation, manage software development, ensure quality and reliability of software solutions, promote AI adoption, and foster continuous improvement.

As a Senior Software Engineer, you'll design and deploy features for a SaaS platform, focusing on both front-end and back-end systems while collaborating with teams to solve logistics challenges.

As a Data Engineer III, you will design and maintain scalable ELT pipelines and data models, develop data infrastructure, optimize storage, and enhance data integrations. Collaborate with cross-functional teams to ensure data quality and leverage AI tools to improve delivery.