Lead Software Engineer, ITC

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.