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About This Role
Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world? Join Apple’s Information Systems and Technology (IS\&T) organization.IS\&T is the engine behind everything Apple does for customers and for the people who build for them. It’s Apple’s central nervous system. Supporting 2\.5 billion active Apple devices, processing billions of secure transactions, and keeping the technology that defines modern life running flawlessly, IS\&T makes the impossible feel effortless.Do you love building solutions to handle global complexity and immense scale? Imagine what you could do here.
AI \& Data Platforms (AiDP) is IS\&T's engine for AI\-powered innovation. The team brings together data, application development, and machine learning \- including generative AI \- along with data services and customer success functions, to help IS\&T build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple.
Description
The people here at Apple don't just craft products \- they build the kind of wonder that's revolutionized entire industries! It's the diversity of those people and their ideas that encourages the innovation that runs through everything we do, from amazing technology to industry\-leading environmental efforts. Join Apple, and help us leave the world better than we found it!
The Data Services OpenSearch team at Apple invites passionate engineers to join our team to develop and contribute to OpenSearch, the leading Open\-Source Search and Analytics suite. Our engineers develop and maintain OpenSearch solutions that powers critical observability, log analytics, and real\-time monitoring for Apple’s critical services across Business units. You will be joining a team of experts working on modern search technologies, distributed systems, and data analytics engineering, helping push the limits of Open\-Source OpenSearch to deliver enterprise\-class performance, scalability, reliability and security. This role offers the opportunity to impact the experiences of millions of users by developing scalable search, monitoring and analytics solutions for Apple’s critical services.
The OpenSearch team at Apple is responsible for developing and managing a highly available, cloud\-based search service. We seek innovative, detail\-oriented engineers who can contribute to a wide range of OpenSearch components, including query parsing, indexing, cluster management, security, scalability, and new feature development. Your contributions will drive the service’s performance, availability, and resilience, supporting a variety of applications and services at Apple.
Success in this role requires a high level of expertise in several of the following:
Understanding of distributed computing concepts, including sharding, data replication, and fault tolerance.
Familiarity with operating system concepts such as process management and network I/O.
Comprehensive knowledge of indexing, searching and analytics concepts (e.g., text analysis, relevancy tuning, and multi\-modal search).
Advanced software engineering skills with Java ecosystem expertise, object\-oriented design principles, and experience in building maintainable, scalable applications.
Hands\-on experience with production deployment workflows, including CI/CD pipelines, container orchestration, version control systems, and distributed systems observability.
Experience with advanced topics like autoscaling, request tracing, and performance tuning in high\-throughput systems.
Strong understanding of testing methodologies and experience with debugging and profiling tools.
The role demands excellent communication skills and the ability to work closely with both the Search Engineering and DevOps teams. A customer\-focused mindset is essential when delivering solutions to internal stakeholders, and collaboration with teams across different global locations is crucial. Mentorship abilities to guide and support junior engineers are also important.","responsibilities":"Develop new features and implement bug fixes in OpenSearch project and related plugins
Develop and maintain Apple\-internal control plane for OpenSearch
Collaborate with the DevOps team in case of production escalations.
Act as a subject matter expert to help our partners and users to understand the technology better
Preferred Qualifications
Strong analytical and problem\-solving capabilities, with a keen attention to detail.
Excellent written and verbal communication skills with proven collaboration abilities
Passionate about Open\-Source contributions and community engagement.
Experience in contributing to or maintaining Open\-Source software projects.
Experience with public clouds (GCP or AWS)
Experience with Kubernetes
Minimum Qualifications
2\+ years of relevant experience in the IT industry, specifically in search engines, distributed systems
High proficiency in languages such as Java, Kotlin, or Go
Strong understanding of data structures, algorithms, and indexing techniques specific to search engines
In\-depth knowledge of search engine internals, ideally with OpenSearch or similar platforms such as OpenSearch or Elasticsearch or Solr
Strong knowledge of Linux/Unix Internals, Systems/Application Design \& Architecture
Expertise in identifying performance bottlenecks and implementing optimization strategies
Bachelor Science in Computer Science or related fields or equivalent work experience
Pay \& Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses \- including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Salary Context
This $139K-$258K range is above the median for AI Product Manager roles in our dataset (median: $191K across 155 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 3,824 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Apple, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $213,800 based on 518 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($198K) sits 7% below the category median. Disclosed range: $139K to $258K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Apple AI Hiring
Apple has 109 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Safety, AI Product Manager. Positions span Cupertino, CA, US, Seattle, WA, US, Austin, TX, US. Compensation range: $207K - $487K.
Location Context
AI roles in Austin pay a median of $218,800 across 493 tracked positions. That's 9% above the national median.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (119) are outnumbered by mid-level (1,813) and senior (1,472) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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