Data Engineer (Agentic AI, LLM Training), G&A Solutions Engineering (GSE)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's no telling what you could accomplish. The G&A Solutions Engineering organization at Apple primarily focuses on creative ways to engineer business solutions to meet growing needs of Apple's Finance, iTunes, Sales, Retail, and Services organizations.
At core, our portfolio comprises of engineered custom solutions to process high volume transactions from Apple Pay, iTunes, Ads, App Store, iPhone Activations to Sales from Retail, Online, and Resellers. These solutions are based on cutting edge enterprise technologies ranging from Distributed Systems, Microservices, Java, Spring/Boot, Oracle, MongoDB, AWS services to AI/ML, Generative AI, and Blockchain. Accurately processing such high volume transactions is our core strength.DescriptionThe iRecon Payments team is seeking a highly motivated Data Engineer with a strong background in Data Science to drive our Agentic AI initiatives. In this role, you will build robust data pipelines, extract features, and curate high-quality datasets to train custom LLMs.
You will navigate complex financial ecosystems to modernize data flows, ensuring accurate reconciliation, invoicing, and payments. You will play a critical role in building GenAI-powered solutions that improve user productivity and operational efficiency.ResponsibilitiesDesign and build scalable data pipelines to enable Agentic AI solutions and custom LLM trainingPerform advanced feature engineering and dataset curation to optimize model performanceBuild upstream/downstream integrations with MCP (Model Context Protocol), Knowledge Graphs, and Vector Databases to support context engineering and retrieval (RAG)Work with large-scale financial transaction data to ensure precision in reconciliation, disbursements, and receiptsPartner with cross-functional teams to translate business requirements into technical AI solutionsMinimum Qualifications2+ years of experience building machine learning solutions using supervised/unsupervised learning, classification, recommendation systems, and clustering algorithmsIn-depth knowledge of transformer architecture, LLMs, and Agentic AI conceptsHands-on experience fine-tuning Large Language Models (LLMs) using PEFT/LoRA for domain-specific tasksProven experience building and extending RAG, MCP (Model Context Protocol), or multi-agent frameworks (e.g., LangChain, LlamaIndex, AutoGen)Bachelor's degree in Computer Science, AI, Machine Learning, or relevant work experiencePreferred Qualifications3+ years of experience building production-grade AI/ML solutions in the FinTech domainStrong written and verbal communication skills with the ability to articulate complex technical conceptsDemonstrated ability to modernize legacy data systems and adapt to new AI architecturesExperience with "Human-in-the-loop" data workflows for financial operationsDemonstrated ability to quickly learn and adapt to new technologies and toolsApple 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 At 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 workplace Learn about reasonable accommodations for job applicants Apple accepts applications to this posting on an ongoing basis.