This role pays less than
58%
of similar roles. Most pay
$172,500–$246,150
— the shaded band above.
At the midpoint, this role pays about
$200k
versus about
$209k
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
1723 open roles
on FindRole.
Listed pay typically runs
$162,500–$272,100
across 1398 roles with salary data.
As an AI Product Development Lead in the Legal and Global Security Operations team, you will drive the rapid development of AI-driven tools that revolutionize legal work processes. Leading a team of AI Product Developers, you will manage the product development lifecycle from discovery to deployment, ensuring solutions are scalable and production-ready. Your daily tasks include building prototypes, integrating AI/ML capabilities into applications, and embedding intelligent features into existing workflows such as matter management and contract lifecycle. You must have extensive experience in product development, AI strategy, and technical program management, along with expertise in modern front-end frameworks and APIs. Preferred qualifications include proficiency in AI-powered legal solutions like compliance and document intelligence, knowledge of LLM orchestration frameworks, and familiarity with RAG architectures and vector databases. This role offers a unique opportunity to bridge the gap between emerging technology and business needs within a large-scale legal tech ecosystem.
Remote (Charlotte, NC)+316 days ago
$200,000–$230,000
Python
REST APIs
Git
Markdown
Data Residency
Access Controls
Audit Logging
Large Language Models
RAG
Orchestration Frameworks
Context Protocols
Model APIs
Construction Industry
Commercial Real Estate
Professional Services Industry
CI/CD
AI
ML
Datacenter
Cloud
Product Management
Systems Thinking
Competitive Analysis
GenAI
ML Accelerators
Hardware
Software
Infrastructure
Performance Analysis
System Layers
End-to-End System Behavior
Problem Solving
Technical Analysis
Customer Workloads
Product Roadmap
Engineering Priorities