Apple
Data Engineer (Agentic AI, LLM Training), G&A Solutions Engineering (GSE)
Austin, Texas · Full-time · Posted Mar 24, 2026
- Experience
- 2+ years required; 3+ years in production-grade FinTech AI/ML solutions preferred.
- Education
- Bachelor's degree in Computer Science, AI, Machine Learning, or relevant work experience.
About the job
Build data pipelines and AI solutions for financial operations, including custom LLM training, reconciliation, invoicing, and payments.
What you'll do
- Design scalable data pipelines and curate datasets for Agentic AI and custom LLM training.
- Engineer features and integrate MCP, Knowledge Graphs, and Vector Databases for context engineering and RAG.
- Work with financial transaction data and cross-functional teams to improve reconciliation, disbursements, receipts, and operational efficiency.
What they ask for
- 2+ years 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 LLMs using PEFT/LoRA; experience building or extending RAG, MCP, or multi-agent frameworks.
- Bachelor's degree in Computer Science, AI, Machine Learning, or relevant work experience.
Nice to have
- 3+ years building production-grade AI/ML solutions in FinTech.
- Experience modernizing legacy data systems or with human-in-the-loop data workflows for financial operations.
Tools
PEFT/LoRA, RAG, MCP (Model Context Protocol), Knowledge Graphs, Vector Databases, LangChain, LlamaIndex, AutoGen
AI focus
Develop Agentic AI solutions, curate training data and fine-tune custom LLMs, and build context engineering and retrieval systems for financial operations.
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