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

Apple Inc

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Work type
On-site
Location
Austin, TX
Posted
56 days ago
Nearby
99+ roles within 25 mi

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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TL;DR · Data Engineer (Agentic AI, LLM Training), G&A Solutions Engineering (GSE)

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As a Data Engineer at Apple’s G&A Solutions Engineering, you will join the iRecon Payments team to drive Agentic AI initiatives by designing scalable data pipelines and curating high-quality datasets for custom Large Language Model training. Your day-to-day responsibilities include advanced feature engineering, integrating with MCP, Knowledge Graphs, and Vector Databases, and working closely with financial transaction data to ensure precise reconciliation and disbursement processes. You will collaborate across teams to translate business requirements into technical AI solutions, leveraging cutting-edge technologies such as Java, Spring/Boot, Oracle, MongoDB, AWS services, and Generative AI frameworks like LangChain and LlamaIndex. This role requires a strong background in Data Science, experience with transformer architecture and fine-tuning LLMs using PEFT/LoRA, and the ability to modernize legacy data systems within the FinTech domain.

Skills

Python Java Spring/Boot AWS Oracle MongoDB Docker Kubernetes Terraform CI/CD LLMs PEFT LoRA RAG MCP LangChain LlamaIndex AutoGen Transformer Architecture Vector Databases

What you'll do

  • Design and build scalable data pipelines for Agentic AI solutions and custom LLM training.
  • Perform advanced feature engineering and dataset curation to enhance model performance.
  • Develop integrations with MCP, Knowledge Graphs, and Vector Databases for context retrieval.
  • Work with large-scale financial transaction data to ensure precise reconciliation processes.
  • Translate business requirements into technical AI solutions for operational efficiency.

What we're looking for

  • 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) for domain-specific tasks.
  • Proven experience building and extending RAG, MCP, or multi-agent frameworks in production environments.
  • Bachelor's degree in Computer Science, AI, Machine Learning, or relevant work experience.
  • 3+ years of experience in FinTech with production-grade AI/ML solutions.
  • Strong communication skills to articulate complex technical concepts effectively.

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