Principal Software Engineer, Generative AI

About the role

Nike is looking for a Principal Software Engineer focused on Generative AI to join its Tech Center in India. The role suits someone who combines deep expertise in software architecture, engineering and AI/ML frameworks with a strategic view of technology decisions, guiding teams through ambiguity and shaping the future of Nike's data-driven platforms.

Key responsibilities

• Lead the architectural vision, technical design and implementation of large-scale data and AI platforms, keeping them robust, secure and performant.
• Champion best practices in software development, agentic AI systems and cloud-based machine learning infrastructure, setting high standards for code quality, reliability and maintainability across teams.
• Mentor and coach senior engineers and provide thought leadership on challenging engineering problems.
• Work with global product and business stakeholders to turn strategy into technology roadmaps aligned with business priorities.
• Promote automation, CI/CD, MLOps and DevOps, test-driven development and agile frameworks.
• Evaluate and integrate emerging technologies and tools.
• Own the end-to-end lifecycle of critical projects, from requirements and design through implementation, monitoring and optimization.
• Ensure platforms meet strict security, privacy and compliance standards.
• Act as a senior technical ambassador for the Tech Center in India with global teams.

Required profile

• Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, Machine Learning, AI systems or a related field; a Master's in AI, ML or Generative AI is highly desirable.
• 12+ years of progressive software engineering experience, including at least five years in a senior leadership or principal engineer capacity.
• Proven track record of leading engineering teams, deploying large-scale machine learning models in production and driving technology projects in an agile environment.
• Strong communication, leadership and stakeholder management skills, and a commitment to diversity and inclusion.

Required skills

• Building and scaling AI platforms, distributed systems and cloud-native AI architectures with AWS SageMaker, Databricks, Azure Machine Learning or Google Vertex AI.
• Python, Java, Scala or Go.
• LLMs, PyTorch, TensorFlow, Spark and cloud-native MLOps tools.
• Kubernetes, Docker and container technologies.
• CI/CD pipelines, infrastructure as code and agentic workflows.