WHO YOU’LL WORK WITH

You’ll be joining a dynamic, fast-paced Global FPE (Foundational Platforms Engineering) team within Nike. Our mission is to build and scale world-class cloud-native platforms, enabling Nike’s data-driven decision-making and intelligent automation capabilities.

This role sits right into AI-driven innovation helping to drive cutting-edge advancements in both analytics and intelligent automation. Collaboration and creativity are at our core, and we are passionate about leveraging cloud-scale data platforms and AI-powered automation to transform business operations.

WHO WE ARE LOOKING FOR

We are seeking a Lead Software Engineer who brings deep expertise in Databricks, AWS Services, Cloud Platforms, and AI-driven automation. You are someone who thrives in building scalable, high-performance data platforms to improve efficiency, insights, and user experience.

Key Skills & Traits:

• 7+ years of experience in AI/ML model development, deployment, and lifecycle management

• Proven track record of architecting large-scale, distributed AI/ML systems

• Deep expertise in LLMs, generative AI, and advanced NLP techniques

• Experience leading MLOps/LLMOps strategy and implementation across teams

• Advanced proficiency in Python, SQL, Spark, and cloud automation

• Hands-on experience with MLFlow

• Experience with Databricks and multi-cloud AI/ML deployments

• Strong background in data engineering, pipeline orchestration, and data governance

• Demonstrated ability to mentor, coach, and lead engineering teams

• Experience with DevOps, CI/CD, containerization (Docker, Kubernetes), and model monitoring/versioning (DVC)

• Excellent communication, stakeholder management, and strategic planning skills

WHAT YOU’LL WORK ON

As a Lead Software Engineer, you will play a crucial role in architecting, modernizing, and leading the development of scalable, production-grade AI/ML platforms.

Core AI/ML engineer Responsibilities:

• Architect and lead the development of scalable, production-grade AI/ML platforms

• Define and enforce best practices for ML model lifecycle, reproducibility, and governance

• Lead cross-team initiatives to drive AI adoption and automation at scale

• Establish best practices for model versioning and reproducibility.

• Design and implement advanced NLP and generative AI solutions

• Manage ML infrastructure on Databricks cloud platform.

• Maintain security and compliance implementations for ML systems.

• Oversee ML infrastructure, cost optimization, and security/compliance for enterprise deployments

• Mentor and guide engineers, fostering a culture of technical excellence and innovation

• Collaborate with product, data, and business teams to align AI solutions with strategic goals

• Evaluate emerging technologies and drive continuous improvement in platform capabilities

• Evangelize AI adoption, helping Nike teams unlock new automation opportunities.