Job Description

WHO YOU'LL WORK WITH

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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

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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

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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.