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.
Skills Required
- 7+ years of software development experience
- Experience with object-oriented development, distributed systems, cloud-native architectures, and AI/data platforms
- Expertise building scalable, highly available distributed systems
- Proficiency in at least one of Java, Python, or Go
- Experience with Kubernetes and Docker
- Experience with relational and NoSQL databases, distributed caches, and messaging pipelines such as Kafka or RabbitMQ
- Experience developing REST or WebSocket APIs
- Experience building and delivering Agentic AI systems, LLM orchestration, prompt engineering, RAG patterns, and agentic architectures
- Understanding of LLM production concerns including grounding, guardrails, AI governance, latency, cost optimization, and observability
- Familiarity with knowledge graphs, vector stores, relational databases, and embedding pipelines
- Advanced knowledge of at least one ML cloud platform, such as AWS SageMaker, Databricks, Azure ML, or GCP
- Proficiency with Infrastructure as Code tools such as Terraform or AWS CloudFormation
- Strong understanding of advanced data modeling and modern data warehouses
- Ability to design scalable, fault-tolerant, and maintainable distributed systems
- Experience developing agentic workflows and AI/LLM-powered enterprise applications
- Knowledge of software security best practices and experience implementing security measures
- Experience with UI/UX design principles and tools such as Figma or Adobe
- Strong collaboration, teamwork, communication, and stakeholder management skills
- Experience building agents with MCP, A2A, LangGraph, CrewAI, or similar frameworks and protocols
Nike Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nike and has not been reviewed or approved by Nike.
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Retirement Support — A 401(k) with a company match is complemented by options such as a Mega Backdoor Roth and deferred compensation for eligible earners. Financial coaching and structured savings programs support long-term financial security.
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Equity Value & Accessibility — An Employee Stock Purchase Plan with a stock discount sits alongside broad-based equity vehicles like RSUs and non-qualified stock options. These avenues expand wealth-building opportunities beyond base pay.
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Parental & Family Support — Paid parental leave includes maternity and paternity time, recently expanded in the U.S. to 16 weeks and extended to part-time retail teammates. Additional supports include childcare assistance at select locations and family-building benefits such as fertility, surrogacy, and adoption.
Nike Insights
What We Do
At NIKE, Inc., we innovate to serve athletes*. Every teammate - from coder to creator - plays a role in making these athletes’ dreams real. Our tech, data, and digital teams push limits every day, building the future of sport and the tools that drive it. Here, curiosity is fuel. Innovation is the game plan. Different perspectives keep us on the offense. You’ll solve challenges worth tackling, grow fast and belong to a team that backs you to do the right thing. Bring your drive. Bring your bold. Let’s move the world, together. Take your first step at nike.com/careers * If you have a body, you’re an athlete.
Why Work With Us
At NIKE, Inc., your dedication fuels the future of sport. There is a sense of pride that comes from representing an iconic brand and shaping its future. Here, we treat every day as a new opportunity to push boundaries, ask tough questions and share whole-hearted convictions. We are a team – united by the belief that anything is possible.
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