Applied AI & Data Engineer - Business & Education

Role Number: 200677759Team: Software and ServicesLocation: Cupertino; SeattlePosted: 2026-08-19SummaryWould you like to help shape how AI and modern data engineering & analytics come together to power Apple's Business and Education products, at a scale that touches millions of enterprises, schools, and the devices and services they depend on?DescriptionApple's Business and Education organization builds the infrastructure, platforms, and services behind Apple's offerings for enterprise and education customers: device management, identity, and subscription services, and the classroom apps built on top of them. Our team owns the data engineering behind all of it, from pipelines and lakehouse architecture through analytics reporting, and we are building a new generation of AI-native capabilities on top: agents, intelligent workflows, and self-serve analytics that change how our Data Engineering, Analytics, and Data Science teams work. The ambition is to define what an AI-first data organization looks like at Apple scale.We are looking for a well-rounded builder. You spent the earlier part of your career deep in software, data, or ML engineering, and the last few years applying that foundation to ship Applied AI products end-to-end. You think architecturally, you know where LLMs and agents earn their keep and where deterministic code is the better answer, and you would rather measure a system's quality than argue about it.Minimum Qualifications8+ years across data engineering, analytics engineering, software engineering, or ML engineering, with the last 3+ years building and shipping Applied AI and agentic LLM systems in production. You are still a builder: you want to spend real time writing code, prototyping, and shipping alongside your team, not only reviewing what others ship.You architect, build, and operate production AI products composed of LLMs, foundation models, agents, and deterministic components, for both human and machine consumers. You have clear judgment on where to infer and where to compute, how to decompose tasks across specialized models, how to orchestrate multi-step reasoning and tool use, and how the system degrades when a model fails.Hands-on fluency with modern LLM and agent frameworks (LangChain, LlamaIndex, Semantic Kernel, Google ADK, or equivalent), vector search (pgvector, FAISS, Pinecone, or equivalent), RAG pipelines, multi-agent coordination, tool invocation, and stateful reasoning. You have moved past vanilla RAG: you know where retrieval breaks, and when to reach for planning, reranking, structured reasoning, fine-tuning, or plain deterministic code instead.Production discipline for AI systems: evaluation harnesses, guardrails, and telemetry that change decisions (offline evals, golden sets, LLM-as-judge, behavioral regression, drift monitoring), and optimization for cost, latency, throughput, and inference quality (model selection, serving decisions, token-spend control, caching, batching, streaming, distillation, quantization, speculative decoding).A foundation in machine learning and deep learning. You understand how transformers and LLMs are trained, fine-tuned, and evaluated, you reason about embeddings, loss functions, and statistical rigor, and you can tell whether a production failure is prompt, retrieval, model, or data.You design and build scalable data platforms on modern cloud-native patterns (Databricks, AWS, or equivalent), and you are as comfortable in the warehouse and the SQL engine (Trino, Presto, Spark) as in the model-serving layer. Proficiency in at least one high-level language (Python, Scala, Java, or Go), strong SQL, and the discipline to write code that is readable, observable in production, and testable at the boundaries.Experience delivering ETL/ELT, streaming, and CDC (change data capture) pipelines with technologies such as Spark, Kafka, and Delta Lake, for both batch and real-time data, along with the workflow orchestration, data quality checks, observability, and alerting that catch breakage before it reaches downstream analytics or AI systems.Knowledge of data modeling patterns and the judgment to pick the right one for a given use case, trading off analytical query performance, governance, and extensibility.A track record of hands-on technical leadership: architecture and design reviews, implementation guidance, production-readiness review, and 3+ years mentoring engineers and prioritizing across concurrent initiatives. You communicate clearly enough across cross-functional teams to influence strategy, and you raise the AI fluency of partner organizations through workshops, playbooks, and design guidance.A product mindset paired with a research sensibility. You read papers, separate signal from hype, work loosely defined problems with meticulous attention to detail, and drive them to completion without sacrificing trust in the result.BS or MS in Computer Science, Information Systems, Artificial Intelligence, Machine Learning, Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience building data and AI systems in production.Preferred QualificationsModel and prompt customization at scale: fine-tuning foundation models, training reward models, building custom retrieval, reranking, or embedding models for domain-specific tasks, and prompt engineering optimized for performance, reliability, and safety.Experience with MLOps and LLMOps: model lifecycle management, deployment pipelines, observability, and prompt and evaluation versioning.Experience building natural-language interfaces over data, text-to-SQL, semantic search, or analytics copilots, for internal or customer-facing use.Experience using AI-native code editors and agent-assisted development environments to improve developer productivity, and establishing guardrails for their responsible use across security, IP protection, compliance, and code quality.Experience with Google Cloud or Azure, stream-processing systems (Apache Flink, Spark Streaming, Kafka Streams), and NoSQL or analytics datastores (Cassandra, MongoDB, Druid, Apache Pinot) for real-time data and real-time AI applications.Experience building AI, machine learning, and experimentation systems in regulated or privacy-sensitive environments.Contributions to open source, research, talks, or technical writing that have shaped how others build AI systems.Prior experience leading or managing engineers, or serving as technical lead across multiple concurrent data and AI projects.Pay & BenefitsAt 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 $184,700 and $324,800, 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 Apple’s 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 Apple’s Employee Stock Purchase Plan. You’ll 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 — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple BenefitsNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.Pay & BenefitsAt 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 $175,000 and $308,500, 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 Apple’s 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 Apple’s Employee Stock Purchase Plan. You’ll 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 — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple BenefitsNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.EEO StatementApple 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 applicantEEO StatementApple 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 applicantAccessibilityAt Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.Learn about accessibility in Apple’s workplaceLearn about reasonable accommodations for job applicantsAccessibilityAt Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.Learn about accessibility in Apple’s workplaceLearn about reasonable accommodations for job applicantsApplication DeadlineApple accepts applications to this posting on an ongoing basis.Application DeadlineApple accepts applications to this posting on an ongoing basis.