Senior Software Engineering Manager - Manufacturing Intelligence, Agentic Systems & Physical AI

Job description

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there is no telling what you could accomplish. Apple’s Manufacturing and Product Operations organization is looking for a hands-on, technically accomplished Senior Software Engineering Manager to lead multiple software engineering teams building the next generation of intelligent manufacturing systems. This organization develops the software platforms, agentic workflows, data infrastructure, and AI-powered applications that support complex manufacturing operations at global scale. The work spans manufacturing process optimization, production planning, quality inspection, equipment intelligence, supply and material workflows, and the emerging use of embodied and physical AI on the factory floor. In this role, you will lead multiple teams responsible for building highly scalable, reliable, and secure systems that connect enterprise applications, manufacturing data, AI models, industrial equipment, and human decision-making. You will establish a cohesive technical strategy across these teams and work closely with manufacturing, operations, quality, test, automation, robotics, machine learning, and data engineering organizations to turn emerging technologies into dependable production capabilities. Building intelligent systems for manufacturing introduces unique challenges: heterogeneous data, rapidly changing factory conditions, high reliability requirements, physical-world constraints, and decisions that can directly affect production. We are looking for an experienced organizational leader with strong software engineering depth, architectural judgment, manufacturing awareness, and a demonstrated ability to build, scale, and align high-performing engineering teams. **Description** As a Senior Software Engineering Manager, you will lead multiple software and systems engineering teams responsible for designing, building, and operating intelligent platforms for manufacturing.You will define the technical strategy, organizational structure, and engineering roadmap across a portfolio of systems that combine distributed software, manufacturing data, machine learning, agentic AI, and physical automation. You will remain deeply engaged in architecture, design reviews, technical trade-offs, and the transition of early prototypes into secure, scalable, and operationally reliable production systems.","responsibilities":"Lead multiple software engineering teams responsible for manufacturing platforms, enterprise integrations, agentic workflows, AI applications and factory-edge systems Establish a unified technical vision, platform strategy and multi-year engineering roadmap across the organization Define clear charters, ownership boundaries, interfaces and operating mechanisms across teams while ensuring that systems are designed as a cohesive platform rather than a collection of independent solutions Develop engineering managers, technical leads and senior individual contributors, creating a strong leadership bench capable of scaling the organization Lead the architecture and development of software platforms supporting manufacturing planning, execution, quality, automation and operational decision-making Build agentic workflows that can retrieve and reason over manufacturing data, use enterprise and factory tools, execute multi-step processes, validate outcomes and appropriately involve human operators Develop the orchestration, tool-calling, memory, context-management, evaluation, observability and governance foundations required to deploy AI agents safely in production Establish software architectures that connect AI systems with manufacturing applications such as ERP, MES, PLM, quality systems, supply-chain platforms, equipment telemetry and engineering data sources Partner with machine learning teams to productionize models for computer vision, anomaly detection, forecasting, optimization, process intelligence and manufacturing knowledge retrieval Enable physical and embodied AI applications involving factory-floor vision, robotics, automated inspection, equipment interaction and closed-loop manufacturing workflows Design systems that bridge cloud, on-premises, edge and factory environments while meeting demanding requirements for latency, availability, security, fault tolerance and data governance Provide architectural guidance for transitioning proofs of concept and research prototypes into robust, maintainable and high-performance production applications Develop reusable platform services, APIs, developer frameworks and integration patterns that enable manufacturing teams to build intelligent workflows efficiently Establish rigorous evaluation and validation frameworks for agentic and AI-driven systems, including task success, tool-use accuracy, hallucination containment, operational safety and measurable business impact Drive engineering excellence across teams through strong design principles, code quality, automated testing, observability, incident management, operational readiness and service ownership Establish consistent engineering processes, development standards, review mechanisms and tooling across the organization Manage dependencies and technical alignment across teams and resolve architectural, ownership and prioritization conflicts Make sound investment and technical trade-offs across model capability, deterministic software, latency, cost, scalability, reliability and implementation complexity Partner with cross-functional leaders to translate manufacturing priorities and operational requirements into a portfolio of clearly defined engineering programs Communicate organizational strategy, technical direction, program health, risks and investment needs to senior leadership and cross-functional stakeholders Build an inclusive, ac