This role pays more than
75%
of similar roles. Most pay
$146,450–$227,500
— the shaded band above.
At the midpoint, this role pays about
$231k
versus about
$187k
for comparable roles.
Based on 240 similar postings.
Employer
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
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 roles with salary data.
The Applied AI Engineer joins the Decision Intelligence team to develop and operate AI solutions that impact sales operations and customer experiences. This role involves translating frontier engineering research into production-ready tools, including SDKs and APIs, while building scalable machine learning systems for internal products. The engineer will design agentic AI systems capable of reasoning across various modalities, build pipelines for multi-modal inputs and semantic routing, and implement safety mechanisms like grounding checks. Key technical requirements include proficiency in Python, FastAPI, LangChain, LlamaIndex, and RESTful API design. Candidates must have experience with LLM APIs, vector databases, and asynchronous programming. The role focuses on solving business problems by integrating context-aware intelligence into decision-making tools, specifically addressing challenges within the sales domain through advanced automation and innovative AI-driven capabilities in a fast-paced environment.
Translate frontier engineering research into practical, scalable features for AI products.
Design and develop agentic AI systems that reason, plan, and act across various tools and modalities.
Convert experimental prototypes into production-ready tools, SDKs, and APIs in partnership with platform engineers.
Build scalable pipelines for multi-modal agent input, memory management, and semantic routing.
Lead technical decision-making on infrastructure components, including safety mechanisms and model monitoring.
Embed context-aware intelligence into decision-making tools by collaborating with data science and sales operations teams.
Prototype and evaluate novel AI approaches to move innovations from concept to production.
What we're looking for
A PhD in Computer Science, Statistics, Mathematics, AI, or a related field with 3+ years of experience in applied AI, machine learning, or statistical modeling.
An MS degree with 6+ years of experience in applied AI, machine learning, or statistical modeling.
Experience with rapid prototyping, reproduction, and validation of research ideas.
Proven ability to translate complex research into scalable, production-level AI solutions and robust code.
Proficiency in Python, FastAPI, LangChain (or similar), context engineering, and RESTful API design.
Hands-on experience with LLM APIs, embeddings, vector databases, and agentic workflows.
Solid grounding in data structures, async programming, and pipeline orchestration.
Ability to communicate technical insights effectively to both technical and non-technical audiences.