WHO YOU’LL WORK WITH
At Nike, we leverage the power of data and technology to serve athletes* around the world. The AI Platform engineering team is at the forefront of this mission—building scalable, secure, and intelligent AI platforms and services, focusing on Generative AI, that powers the decision-making and personalized experiences across the Nike ecosystem.

WHO WE ARE LOOKING FOR
We are looking for a passionate software engineers with a mission for designing and building robust AI platforms and services with Scale, performance, Cost optimizations in mind. You thrive in a fast-paced, collaborative environment and have a proven track record of delivering scalable and reliable software platforms and services.

WHAT YOU’LL WORK ON

• Design, build, deploy, and own complete, scalable, and reliable Agentic AI and software platforms and services.
• Lead the technical design of Distributed systems and Agentic AI services, DevOps using Kubernetes
• Build reusable frameworks, libraries, and data management tools to improve productivity.
• Optimize performance and cost-efficiency of ML workflows and compute layers.
• Collaborate with stakeholders such as ML/MLOps Engineers, Business domain Technology teams, and product managers to understand and translate the business requirements into technical solutions.
• Lead the development and production of agentic and AI/LLM powered enterprise systems.
• Collaborate with Product Managers to ensure the experiences are optimized for usability and performance.
• Implement security best practices to protect data and ensure compliance with industry standards.
• Develop and maintain automated tests to ensure the quality and reliability of the software.
• Provide technical leadership and mentorship to junior engineers.
• Ensure the uptime, reliability, and monitoring of the systems you build and own.
• 7+ years of experience in software development, with a strong foundation in object-oriented development, distributed systems, cloud-native architectures, and AI/Data platforms.
• Strong expertise in building scalable and HA distributed systems, OOPS language like Java/Python/Go, Container technologies like Kubernetes/Docker, RDBMS/NoSQL databases, Distributed caches, Messaging pipelines like Kafka/RabbitMQ, REST or WebSocket based APIs
• Experience building Agentic AI systems, LLM orchestration, prompt engineering, RAG patterns, and agentic architectures. You have built and delivered AI-powered solutions, not just prototypes.
• Nice to have - Experience building agents using modern frameworks and protocols (MCP, A2A, LangGraph, Crew AI, or similar); you've gone beyond tutorials and built something meaningful, whether in production, a significant internal project, or a customer-facing PoC.
• Understanding LLM production concerns: grounding, guardrails, AI Governance, latency, cost optimization, and observability.
• Familiarity with knowledge graphs, vector stores, relational databases, and embedding pipelines.
• Advanced knowledge of any one or more ML cloud platform (AWS SageMaker, Databricks, Azure ML, GCP) and its ecosystem of services.
• Proficiency with Infrastructure as Code (IaC) tools like Terraform or AWS CloudFormation.
• Strong understanding of advanced data modeling techniques and modern data warehouses.
• Ability to design scalable, fault-tolerant, and maintainable distributed systems.
• A strong familiarity and development experiences with agentic workflow and AI/LLM powered enterprise applications.
• Experience with UI/UX design principles and tools such as Figma or Adobe.
• Knowledge of security best practice and experience implementing security measures in software development.
• Strong collaboration and teamwork skills, with the ability to work effectively in a cross-functional team.
• Excellent spoken and written communication and stakeholder management skills.