Apple's Developer Experience Platform team is building an AI-powered developer platform with autonomous agents and workflows. This hands-on engineering role involves designing and maintaining backend services and orchestration systems for multi-agent AI workflows, integrating LLMs into developer tools, and collaborating with researchers and engineers to bring new AI capabilities to production.
Responsibilities
Design and maintain backend services and orchestration systems that power multi-agent AI workflows.
Build reliable systems that integrate large language models (LLMs) into developer tools and services.
Work on cloud deployments, CI/CD, and MLOps practices to keep AI services reliable and scalable.
Collaborate with researchers and engineers to bring new AI capabilities into production.
Partner with developers to understand their needs and improve the experience of using AI-powered tools.
Requirements
Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (or equivalent practical experience).
4+ years of industry experience in software engineering or machine learning.
Hands-on experience building AI agents with Large Language Models (LLMs), including Retrieval-Augmented Generation (RAG), using frameworks such as LangChain, LangGraph, Pydantic AI, or CrewAI.
Apple Inc. is an American multinational technology company that designs, develops, and sells consumer electronics, computer software, and online services. Its core products include the iPhone, iPad, Mac computers, Apple Watch, and various digital services.
Strong programming skills in Python, Java, Go, Node.js, or TypeScript, with solid experience designing and developing distributed systems, backend services, and APIs in production environments.
Nice to Have
Familiarity with deploying and operating services in cloud environments (AWS, GCP, or Azure), including containerization (Docker) and orchestration (Kubernetes).
Experience with CI/CD pipelines and MLOps practices for deploying, scaling, and monitoring LLM-powered services.
Background in building REST or GraphQL APIs, microservices, and event-driven systems.
Knowledge of vector databases, memory systems, and human-in-the-loop workflows.
Strong collaboration skills with the ability to work effectively across ML research, platform engineering, and product teams.
Tech Stack
PythonLLMRAGMLOpsTypeScriptAWSGoAzureGCPKubernetesDockerLangChainLangGraphGraphQLJavaNode.jsCrewAIPydantic AI