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Gen AI Software Engineer

Job in Austin, Travis County, Texas, 78719, USA
Listing for: Apple Inc.
Full Time position
Listed on 2026-02-17
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer, Software Engineer
Job Description & How to Apply Below
Do you love creating elegant solutions to highly complex challenges? Do you intrinsically see the importance in every detail? As part of our Silicon Technologies group, you'll help build AI-driven solutions that solve pressing business challenges. You'll ensure Apple products and services can seamlessly and efficiently handle the tasks that make them beloved by millions. Joining this group means you'll be responsible for crafting and building the technology that fuels Apple's devices.

We are looking for an individual who is passionate about joining Apple's engineering team as a Gen AI Software Engineer to design and build generative AI systems and agentic workflows for our  this highly visible role, your primary responsibilities will include:

* Designing and implementing generative AI systems including multi-agent workflows, tool calling architectures, LLM orchestration patterns, and reusable AI components

* Building agentic AI solutions that coordinate multiple AI services and tools to solve complex domain-specific problems

* Collaborating with our internal multi-functional teams as well as the AIML organization at Apple to understand domain-specific needs and architect appropriate AI solutions

* Enabling the organization to leverage AI capabilities and drive efficiency in chip delivery

Hands-on experience with agentic AI frameworks (e.g. Lang Graph, Auto Gen, CrewAI) for building multi-step reasoning and tool-using agents

Familiarity with integrating Model Context Protocol (MCP) into AI workflows

Experience building evaluation frameworks for AI systems (retrieval quality, agent performance, LLM outputs)

Experience in designing and implementing information retrieval systems using embeddings, vector stores (e.g. Milvus, Qdrant), or similarity match u0026 ranking techniques

Designed and optimized RESTful services

Comfortable working within Linux/Unix environments

Array
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