Data Engineer (Agentic AI, LLM Training), G&A Solutions Engineering (GSE)

Apple Inc.; Austin (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Apple Inc. is seeking a Data Engineer for the Agentic AI, LLM Training initiative under the G&A Solutions Engineering group in Austin, TX.

You will build robust data pipelines, extract features, and curate datasets to train custom LLMs, handling high-volume financial data to improve reconciliation, invoicing, and payments. You will work with MCP, Knowledge Graphs, and vector databases to support context engineering and retrieval.

Qualifications

• 2+ years building ML solutions with supervised/unsupervised methods.
• Strong understanding of transformer architectures and LLMs.
• Hands-on PEFT/LoRA tuning for domain tasks.
• Experience with RAG, MCP or multi-agent frameworks (LangChain, LlamaIndex, AutoGen).
• Bachelor’s degree in CS/AI/ML or equivalent work experience.

Responsibilities

• Design scalable data pipelines to enable Agentic AI and LLM training.
• Perform feature engineering and dataset curation for model improvement.
• Integrate MCP, knowledge graphs, and vector DBs for context retrieval.
• Work with large-scale financial data to ensure accuracy in reconciliation and payments.
• Collaborate with cross-functional teams to translate business needs into AI solutions.

Skills

ML experience

Transformer/LLM knowledge

PEFT/LoRA fine-tuning

Agentic AI concepts

Cross-functional collaboration

Education

Bachelor’s degree in CS/AI/ML

Tools

LangChain

LlamaIndex

AutoGen

MCP (Model Context Protocol)

Vector Databases

Knowledge Graphs

Job description

Data Engineer (Agentic AI, LLM Training), G&A Solutions Engineering (GSE)

Austin, Texas, United States Software and Services

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.

Description

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 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

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

Preferred Qualifications

• 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

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

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.

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Apple accepts applications to this posting on an ongoing basis.