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Gen AI Software Engineer

Apple - Cupertino, CA

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Job Description

Role Number: 200626218-0836 Summary Do you love creating elegant solutions to highly complex challenges? Do you intrinsically see the importance in every detail? As part of our Silicon Technologies group, you'll help build AI-driven solutions that solve pressing business challenges. You'll ensure Apple products and services can seamlessly and efficiently handle the tasks that make them beloved by millions. Joining this group means you'll be responsible for crafting and building the technology that fuels Apple's devices.We are looking for an individual who is passionate about joining Apple's engineering team as a Gen AI Software Engineer to design and build generative AI systems and agentic workflows for our domains. Description In this highly visible role, your primary responsibilities will include:- Designing and implementing generative AI systems including multi-agent workflows, tool calling architectures, LLM orchestration patterns, and reusable AI components- Building agentic AI solutions that coordinate multiple AI services and tools to solve complex domain-specific problems- Collaborating with our internal multi-functional teams as well as the AIML organization at Apple to understand domain-specific needs and architect appropriate AI solutions- Enabling the organization to leverage AI capabilities and drive efficiency in chip delivery Minimum Qualifications + Python programming experience + Experience building generative AI applications using LLMs and vector databases + Knowledge of current Gen AI research and techniques in one or more of the following areas: RAG systems, Agentic AI (multi-agent orchestration, tool calling), or Prompt Engineering + Minimum requirement of BS and 10 years of relevant industry experience. Preferred Qualifications + Hands-on experience with agentic AI frameworks (e.g. LangGraph, AutoGen, CrewAI) for building multi-step reasoning and tool-using agents + Familiarity with integrating Model Context Protocol (MCP) into AI workflows + Experience building evaluation frameworks for AI systems (retrieval quality, agent performance, LLM outputs) + Experience in designing and implementing information retrieval systems using embeddings, vector stores (e.g. Milvus, Qdrant), or similarity match & ranking techniques + Designed and optimized RESTful services + Comfortable working within Linux/Unix environments Pay & Benefits At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Appleu2019s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Appleu2019s Employee Stock Purchase Plan. Youu2019ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses u2014 including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. ( Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (.

Created: 2025-10-22

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