About The Position

Join Apple’s Information Systems and Technology (IS&T) organization, the engine behind everything Apple does for customers and for the people who build for them. IS&T supports 2.5 billion active Apple devices, processes billions of secure transactions, and keeps the technology that defines modern life running flawlessly. Sales and Operations Engineering is part of IS&T and drives the technology behind Apple's global operations, sales, and supply chain. The team connects the systems that move products from factory to customer — bridging sales platforms with the operational infrastructure that keeps Apple running at scale and ensuring Apple's technology and business priorities move in lockstep. Our team builds mission-critical enterprise platforms that coordinate complex global operations across worldwide cross-functional organizations. We operate at the intersection of supply chain domain complexity, modern distributed architecture, and cutting-edge artificial intelligence, solving hard engineering problems around temporal dependency modeling, real-time collaboration, and automated schedule optimization.

Requirements

  • B.S. in Computer Science, Computer Engineering, or a related technical field, or equivalent professional work experience.
  • 5+ years proven experience developing software in a professional capacity.
  • 2+ years proven experience with Java, including proficiency in concurrency, memory management, and performance optimization techniques.
  • Proficiency in OOP principles, data structures, algorithms, and software design patterns (e.g. GoF), with a proven focus on implementing testable, maintainable, and extensible backend code
  • Experience building production applications with the Spring ecosystem (e.g. Spring Boot, Spring MVC, Spring Security, Spring Data, Spring Cloud, etc.), including proficiency in dependency injection, auto-configuration, reactive programming with WebFlux, and designing microservices using Spring-based patterns.
  • Experience designing, implementing, and shipping high-scale, high-performance, highly available, fault-tolerant, and secure cloud-based distributed systems.
  • Experience with AI/ML technologies, including building and deploying production ML models using modern frameworks (e.g. TensorFlow, PyTorch, scikit-learn, etc.) and applying supervised/unsupervised learning techniques to real-world problems.
  • Track record of leading software projects within a team as a tech lead (TL), while mentoring software engineers.
  • Hands-on experience leveraging GenAI coding tools (e.g., Claude, Copilot, Codex) to accelerate the software development lifecycle, enhance code quality, and streamline debugging and testing processes.
  • Experience with Natural Language Processing and Generative AI systems, including Large Language Models (LLMs), Retrieval Augmented Generation (RAG) architectures, embedding pipelines, vector databases (e.g. Pinecone, Weaviate, pgvector, etc.), fine-tuning, and prompt engineering for production applications.
  • Experience using relational (e.g. Oracle, Postgres, MySQL, etc.) and NoSQL (e.g. Cassandra, MongoDB, etc.) databases, including proficiency in schema design, query optimization, performance tuning (e.g. execution plan analysis, indexing strategy, and query rewriting).

Nice To Haves

  • Longer experience preferred.

Responsibilities

  • Lead the technical design, evolution, and delivery of high-throughput distributed systems that coordinate complex, multi-tier operational schedules and readiness pipelines worldwide.
  • Lead the end-to-end architecture and implementation of our next-generation supply chain planning platform, ensuring high availability, horizontal scalability, and sub-second responsiveness.
  • Architect distributed backend microservices using Java and Python to handle complex temporal data modeling, multi-dimensional milestone dependencies, and state versioning workflows.
  • Design and implement real-time collaborative planning workspaces using React, TypeScript, and custom timeline visualizations (such as D3.js) to support concurrent multi-user planning.
  • Partner closely with Operations Research Data Scientists to integrate mathematical optimization solvers (such as OR-Tools) and AI inference engines into production workflows for automated schedule generation and feasibility validation.
  • Build event-driven data streaming pipelines and integration contracts using Apache Kafka and Snowflake to synchronize upstream operational inputs with downstream enterprise execution systems in real time.
  • Model flexible, performant relational schemas and append-only event stores for comprehensive auditability, state diffing, and scenario sandboxing.
  • Establish technical benchmarks, CI/CD automation, testing frameworks, and observability telemetry across the entire platform ecosystem.
  • Mentor software engineers through architectural reviews, code reviews, and design sessions while aligning technical roadmaps with global business objectives.
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