Who You'll Work With
You'll join the Nike Marketing Technology platforms team focused on building next-generation Digital Asset Management (DAM) systems powering Nike's global marketing ecosystem. The team partners closely with product, content ops, and engineering teams to enable scalable, AI-driven workflows across markets and languages.
Who We Are Looking For
As a Software Engineer II, you are an individual contributor who delivers high-quality, scalable software while continuously improving your craft. You take ownership of features end-to-end—from design to production—and collaborate effectively with senior engineers and product partners to translate business requirements into technical solutions. You are comfortable working in distributed systems and cloud-native environments and are eager to learn modern technologies including AI-enabled development workflows. You write clean, maintainable code, contribute to code reviews, and proactively identify areas for improvement. You bring a strong problem-solving mindset and are motivated to grow into a senior engineering role.
In addition to the requirements described above, successful candidates will exhibit the following:
2–5 years of experience building scalable backend services or full-stack applications
Proficiency in Java/Spring Boot or similar backend stack
Experience with REST APIs and microservices architecture
Familiarity with frontend technologies (React, JavaScript, HTML/CSS)
Working knowledge of AWS/cloud-native services (or equivalent)
What You'll Work On
You will contribute to building scalable services and data pipelines that power Nike's Digital Asset Management platform for content planning and asset management.
Your responsibilities will include:
Developing scalable APIs and services for content orchestration and DAM workflows
Contributing to frontend features for internal tools used by global teams
Writing unit and integration tests to ensure system reliability
Supporting platform operations, debugging issues, and improving system stability
Collaborating with cross-functional teams to deliver end-to-end features
Learning and adopting AI-assisted development practices and platform capabilities
