Senior Agentic AI Platform Engineer

Apple Inc.

Austin (TX)

On-site

USD 150,000 - 190,000

Full time

14 days+

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Job summary

Apple Inc. in Austin, Texas is seeking a Sr Software Engineer to help design and implement the developer experience platform for agentic AI. You will contribute to building the backbone of our AI-powered developer tools that accelerate app development across Apple.

The role requires strong backend and distributed systems expertise, hands-on experience with AI agents and LLMs, and a focus on reliability and scale in production environments.

Qualifications

  • Bachelor’s degree in Computer Science, AI, ML, or related field, or equivalent practical experience.
  • 4+ years of industry experience in software engineering or machine learning.
  • Hands-on experience building AI agents with LLMs, including RAG, using LangChain, LangGraph, Pydantic AI, or CrewAI.
  • Strong programming skills in multiple languages (Python, Java, Go, Node.js, TypeScript) with distributed systems and backend APIs in production.

Responsibilities

  • Design and maintain backend services and orchestration systems powering multi-agent AI workflows.
  • Build reliable systems that integrate large language models into developer tools and services.
  • Work on cloud deployments, CI/CD, and MLOps to keep AI services reliable and scalable.
  • Collaborate with researchers and engineers to bring new AI capabilities into production.
  • Partner with developers to improve the experience of using AI-powered tools.

Skills

Software engineering
Machine learning
Distributed systems
AI agents

Education

Bachelor’s degree or equivalent

Tools

LangChain
LangGraph
Pydantic AI
CrewAI
Docker
Kubernetes

Job description

Apple Inc. in Austin, Texas is seeking a Sr Software Engineer to help design and implement the developer experience platform for agentic AI. You will contribute to building the backbone of our AI-powered developer tools that accelerate app development across Apple.

The role requires strong backend and distributed systems expertise, hands-on experience with AI agents and LLMs, and a focus on reliability and scale in production environments.

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