Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world? Join Apple’s Information Systems and Technology (IS\u0026T) organization. IS\u0026T is the engine behind everything Apple does for customers and for the people who build for them. It’s Apple’s central nervous system. Supporting 2.5 billion active Apple devices, processing billions of secure transactions, and keeping the technology that defines modern life running flawlessly, IS\u0026T makes the impossible feel effortless.Do you love building solutions to handle global complexity and immense scale? Imagine what you could do here. \\n\\nApple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, and experience we deliver is the result of us making each other"s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It"s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you"ll do more than join something: You"ll add something.\\n\\nOn this team, you"ll help reshape how Apple works by bringing the power of generative and agentic AI to the processes behind our business. If you love solving hard problems, partnering closely with the people you build for, and seeing your work make a real difference every day, we"d love to hear from you.\\n\\n\\n
We are looking for a strong Senior Software Engineer with experience in technology transformation and operating model setup to design, build, and oversee the implementation of AI automation solutions. In this role, you will streamline business processes using generative AI, agentic AI, workflow orchestration, and process automation. You will work closely with business functions to understand how they work, turn their pain points into scalable production solutions, and measure the impact those solutions deliver.\\n
Tailored Implementation: Customize GenAI and process automation platforms so they work well in each business function"s environment.\\nAI and System Integration: Deploy and operationalize AI agents, LLM-powered workflows, and complex data models in production environments, integrating with enterprise systems and APIs.\\nOperating Model Setup: Define and establish the automation operating model, including intake, prioritization, delivery standards, governance, and support handoff.\\nReusable Frameworks: Build reusable components, templates, and patterns so automation can scale across business functions.\\nEvaluation and Quality: Design evaluation frameworks to measure accuracy, reliability, hallucination rates, and drift for GenAI and agentic solutions.\\nObservability and Operations: Build monitoring, logging, alerting, and cost tracking for AI workflows running in production.\\nResponsible AI and Governance: Ensure solutions meet privacy, security, compliance, and responsible AI standards, including data handling, access controls, and human-in-the-loop safeguards.\\nTechnical Troubleshooting: Solve complex technical blockers and debug issues during deployment, acting as a liaison between business functions and the product engineering team.\\nBusiness Function Embedding: Work alongside business functions to deeply understand their workflows, pain points, and opportunities for automation.\\nValue Measurement: Define and track success metrics such as hours saved, cycle time reduction, error rates, and adoption to quantify business impact and ROI.\\nStakeholder Engagement: Act as a technical thought leader, influencing senior leadership decisions through data-driven insights and executive storytelling.\\nCross-Functional Leadership: Lead cross-functional global initiatives across engineering, IT, and operations, and manage vendor performance so projects are delivered on time, on budget, and with high quality.\\nChange Management and Adoption: Partner with business teams to drive user adoption, training, and change management.\\nProduct Feedback: Feed customer insights back to the internal development team to improve the core platform.\\nTechnology and Innovation: Evaluate emerging technologies such as agentic AI, LLMs, and cloud-native services to drive continuous improvement in efficiency and reliability.\\nMentorship: Mentor engineers and promote engineering best practices through code reviews and design reviews.\\n
6+ years of experience in application development, with a proven track record of building highly reliable and scalable systems.\\nStrong proficiency in Java and/or Python, with a good understanding of object-oriented techniques, algorithms, design patterns, and reusable component design.\\nHands-on experience building solutions with GenAI, including LLM application patterns such as retrieval-augmented generation (RAG), prompt engineering, tool/function calling, embeddings, and vector databases.\\nProven experience tailoring GenAI and process automation platforms to complex business environments.\\nExperience designing APIs and integrating with enterprise systems (e.g., REST, event-driven architectures, ERP, CRM, or ITSM platforms).\\nExperience with cloud platforms, containerization, and CI/CD.\\nStrong analysis, problem-solving, and troubleshooting skills.\\nExperience as a technical thought leader, influencing leadership decisions through data-driven insights and executive storytelling.\\n
Experience building agentic AI solutions, including agent frameworks and protocols (e.g., LangGraph, MCP) and multi-agent orchestration.\\nExperience with workflow orchestration or process automation platforms (e.g., Temporal, Airflow, Camunda, UiPath, ServiceNow).\\nFamiliarity with LLMOps/MLOps practices such as model versioning, evaluation pipelines, and guardrails.\\nExperience with process mining or process discovery tools.\\nTrack record of taking AI automation from proof of concept to scaled production.\\nGood understanding of relational and NoSQL database technologies.\\nCommitment to delivering high-quality code with unit and integration tests.\\nHands-on experience with Agile methodologies.\\nPassion for the customer, user experience, and acting on user feedback.\\nExcellent prioritization and scheduling skills, and the ability to handle ambiguity.\\nAttention to detail and the ability to learn new applications and technologies quickly.\\nAbility to thrive in a collaborative environment, both within your team and across groups.\\nPassion for operational excellence and clear communication with cross-functional teams.\\nBS/MS in Computer Science, Software Engineering, or equivalent experience.
We are looking for a strong Senior Software Engineer with experience in technology transformation and operating model setup to design, build, and oversee the implementation of AI automation solutions. In this role, you will streamline business processes using generative AI, agentic AI, workflow orchestration, and process automation. You will work closely with business functions to understand how they work, turn their pain points into scalable production solutions, and measure the impact those solutions deliver.\\n
Tailored Implementation: Customize GenAI and process automation platforms so they work well in each business function"s environment.\\nAI and System Integration: Deploy and operationalize AI agents, LLM-powered workflows, and complex data models in production environments, integrating with enterprise systems and APIs.\\nOperating Model Setup: Define and establish the automation operating model, including intake, prioritization, delivery standards, governance, and support handoff.\\nReusable Frameworks: Build reusable components, templates, and patterns so automation can scale across business functions.\\nEvaluation and Quality: Design evaluation frameworks to measure accuracy, reliability, hallucination rates, and drift for GenAI and agentic solutions.\\nObservability and Operations: Build monitoring, logging, alerting, and cost tracking for AI workflows running in production.\\nResponsible AI and Governance: Ensure solutions meet privacy, security, compliance, and responsible AI standards, including data handling, access controls, and human-in-the-loop safeguards.\\nTechnical Troubleshooting: Solve complex technical blockers and debug issues during deployment, acting as a liaison between business functions and the product engineering team.\\nBusiness Function Embedding: Work alongside business functions to deeply understand their workflows, pain points, and opportunities for automation.\\nValue Measurement: Define and track success metrics such as hours saved, cycle time reduction, error rates, and adoption to quantify business impact and ROI.\\nStakeholder Engagement: Act as a technical thought leader, influencing senior leadership decisions through data-driven insights and executive storytelling.\\nCross-Functional Leadership: Lead cross-functional global initiatives across engineering, IT, and operations, and manage vendor performance so projects are delivered on time, on budget, and with high quality.\\nChange Management and Adoption: Partner with business teams to drive user adoption, training, and change management.\\nProduct Feedback: Feed customer insights back to the internal development team to improve the core platform.\\nTechnology and Innovation: Evaluate emerging technologies such as agentic AI, LLMs, and cloud-native services to drive continuous improvement in efficiency and reliability.\\nMentorship: Mentor engineers and promote engineering best practices through code reviews and design reviews.\\n
6+ years of experience in application development, with a proven track record of building highly reliable and scalable systems.\\nStrong proficiency in Java and/or Python, with a good understanding of object-oriented techniques, algorithms, design patterns, and reusable component design.\\nHands-on experience building solutions with GenAI, including LLM application patterns such as retrieval-augmented generation (RAG), prompt engineering, tool/function calling, embeddings, and vector databases.\\nProven experience tailoring GenAI and process automation platforms to complex business environments.\\nExperience designing APIs and integrating with enterprise systems (e.g., REST, event-driven architectures, ERP, CRM, or ITSM platforms).\\nExperience with cloud platforms, containerization, and CI/CD.\\nStrong analysis, problem-solving, and troubleshooting skills.\\nExperience as a technical thought leader, influencing leadership decisions through data-driven insights and executive storytelling.\\n
Experience building agentic AI solutions, including agent frameworks and protocols (e.g., LangGraph, MCP) and multi-agent orchestration.\\nExperience with workflow orchestration or process automation platforms (e.g., Temporal, Airflow, Camunda, UiPath, ServiceNow).\\nFamiliarity with LLMOps/MLOps practices such as model versioning, evaluation pipelines, and guardrails.\\nExperience with process mining or process discovery tools.\\nTrack record of taking AI automation from proof of concept to scaled production.\\nGood understanding of relational and NoSQL database technologies.\\nCommitment to delivering high-quality code with unit and integration tests.\\nHands-on experience with Agile methodologies.\\nPassion for the customer, user experience, and acting on user feedback.\\nExcellent prioritization and scheduling skills, and the ability to handle ambiguity.\\nAttention to detail and the ability to learn new applications and technologies quickly.\\nAbility to thrive in a collaborative environment, both within your team and across groups.\\nPassion for operational excellence and clear communication with cross-functional teams.\\nBS/MS in Computer Science, Software Engineering, or equivalent experience.