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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Apple Inc. - **Location:** Austin, TX, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, ITunes, App Store (IOS), Databases, Data Systems, Distributed Systems, Graph Database, Spring Framework, Machine Learning, MongoDB, Oracle (Applications), Recommender Systems, Blockchain, Data Streaming, Transaction Data, Feature Engineering, Large Language Models, Multi-Agent Systems, Generative AI, Build Management, Information Technology, Data Analytics, Virtual Agents, Data Pipelines, Unsupervised Learning, Microservices - **Published:** September 1, 2026 - **Apply:** https://www.themuse.com/jobs/apple/data-engineer-agentic-ai-llm-training-ga-solutions-engineering-gse-7d2437 ## About the Role 3+ years of experience building production-grade AI/ML solutions in the FinTech domain Strong written and verbal communication skills with the ability to articulate complex technical concepts Demonstrated ability to modernize legacy data systems and adapt to new AI architectures Experience with "Human-in-the-loop" data workflows for financial operations Demonstrated ability to quickly learn and adapt to new technologies and tools Minimum Qualifications 2+ years of experience building machine learning solutions using supervised/unsupervised learning, classification, recommendation systems, and clustering algorithms In-depth knowledge of transformer architecture, LLMs, and Agentic AI concepts Hands-on experience fine-tuning Large Language Models (LLMs) using PEFT/LoRA for domain-specific tasks Proven 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 experience ## 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'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., The 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. Responsibilities: Design and build scalable data pipelines to enable Agentic AI solutions and custom LLM training Perform advanced feature engineering and dataset curation to optimize model performance Build upstream/downstream integrations with MCP (Model Context Protocol), Knowledge Graphs, and Vector, Get Data and Analytics jobs in Austin, TX delivered to your inbox every week. 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Databases to support context engineering and retrieval (RAG) Work with large-scale financial transaction data to ensure precision in reconciliation, disbursements, and receipts Partner with cross-functional teams to translate business requirements into technical AI solutions ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [40 Minutes to Build a Serverless COVID-19 REST and GraphQL APIs](https://www.wearedevelopers.com/videos/208-40-minutes-to-build-a-serverless-covid-19-rest-and-graphql-apis) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)