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Job Overview:
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As a Product Manager in Arm’s Cloud AI Business Unit, you will help drive Arm’s compute subsystem products for next\-generation data center infrastructure.
This highly technical role spans product definition, lifecycle management, and partner enablement. You will work closely with engineering, architecture, and customer\-facing teams to evolve existing products, define requirements for future products, and help leading hyperscalers and technology partners successfully embrace and implement Arm technology.
Key Responsibilities
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- Product Definition: Define and refine compute subsystem requirements, translating customer needs, technology trends, and product strategy into clear engineering priorities.
- Product Lifecycle: Handle and evolve existing computing module offerings, driving improvements and addressing partner needs throughout the product lifecycle.
- Partner Enablement: Collaborate with engineering and client\-facing teams to support partners integrating Arm technology, from RTL through physical implementation.
- Product Insights: Bring insights from partner deployments and existing products into product priorities and future product direction.
- Multi\-functional Leadership: Drive alignment across product, architecture, engineering, program, and commercial teams on priorities, tradeoffs, and execution.
Required Skills and Experience
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- Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
- 5\+ years of experience with processors, SoCs, compute subsystems, or related hardware technologies.
- Strong understanding of the hardware development lifecycle and ability to engage with engineering teams across architecture, RTL, verification, performance, and physical implementation.
- Ability to understand sophisticated technical problems, evaluate tradeoffs, and translate product needs into actionable requirements and priorities.
- Strong cross\-functional teamwork and communication skills.
Desirable Experience
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- Experience working with customers or technology partners on technical requirements, product adoption, or implementation.
- Experience with Arm\-based processors, compute subsystems, or server technologies.
- Experience with data center, cloud infrastructure, networking, HPC, or AI compute platforms.
- Familiarity with system architecture, including compute, memory, interconnect, I/O, acceleration, or system IP.
- Experience defining product requirements or influencing hardware product roadmaps.
- Product management, systems engineering, solutions architecture, applications engineering, or similar technical product experience
In return: You will get to apply your engineering skills to build support for the technologies and influence millions of devices for years to come. You will be able to drive and bring your ideas to a wider group of our leading experts, build your technical leadership and influencing skills and build towards becoming an established and recognized authority within the existing team.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
In Return:
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Joining Arm means stepping into a career‑defining opportunity. You’ll occupy a central role in the company’s most critical initiatives. These initiatives build how Arm innovates, scales, and partners globally.
Additional Information
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Please note this role does not meet the eligibility requirements for sponsorship, and therefore the successful candidate must have the right to work in the US without relying on sponsorship by Arm.
10x Mindset at Arm
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At Arm, we believe progress happens when people are empowered to think bigger and push beyond what seems possible. Our 10x mindset is about curiosity, ambition and creating impact that will be used by millions. We learn fast, prioritise collaboration and turn bold ideas into real technology. We look for people who are inspired by this way of working and want to grow in an environment where bold ideas are welcomed. Read more about how we bring the 10x mindset to life on the Arm blog.
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Accommodations at Arm
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At Arm, we want to build extraordinary teams. If you need an adjustment or an accommodation during the recruitment process, please email [email protected]. To note, by sending us the requested information, you consent to its use by Arm to arrange for appropriate accommodations. All accommodation or adjustment requests will be treated with confidentiality, and information concerning these requests will only be disclosed as necessary to provide the accommodation. Although this is not an exhaustive list, examples of support include breaks between interviews, having documents read aloud, or office accessibility. Please email us about anything we can do to accommodate you during the recruitment process.
Equal Opportunities at Arm
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Arm is an equal opportunity employer, committed to providing an environment of mutual respect where equal opportunities are available to all applicants and colleagues. We are a diverse organization of dedicated and innovative individuals, and don’t discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Hybrid Working at Arm
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Arm’s hybrid approach to working is centred around flexibility, where we split our time between the office and other locations to get our work done. Within that framework, we empower groups and teams to determine their own particular hybrid working pattern, depending on the work and the team’s needs. Details of what this means for each role will be shared upon application. In some cases, the flexibility we can offer is limited by local legal, regulatory, tax, or other considerations, and where this is the case, we will collaborate with you to find the best solution. Please talk to us to find out more about what this could look like for you
Salary Range:
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$207,800\-$281,200 per year
We value people as individuals and our dedication is to reward people competitively and equitably for the work they do and the skills and experience they bring to Arm. Salary is only one component of Arm's offering. The total reward package will be shared with candidates during the recruitment and selection process.
Our 10x Mindset
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At Arm, we believe progress happens when people are empowered to think bigger and push beyond what seems possible. Our 10x mindset is about curiosity, ambition and creating impact that will be used by millions. We learn fast, prioritise collaboration and turn bold ideas into real technology. We look for people who are inspired by this way of working and want to grow in an environment where bold ideas are welcomed. Discover how the 10x mindset shapes life at Arm: https://careers.arm.com/10x\-mindset
Use of AI in Your Application
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At Arm, we embrace the benefits AI can bring, including in recruitment. You may use AI to support your preparation, such as improving the clarity of written responses, practicing interview questions, or learning more about our industry. However, your application, and interview responses must reflect your own thinking, experience, and abilities. We want to understand your authentic perspective, creativity, and approach to problem solving. As such, you may not use AI to complete assigned tasks as part of any assessments. If you plan to use AI\-supported or assistive technologies as part of a reasonable adjustment, please contact [email protected] so we can support you.
Recruitment Adjustments and Accommodations
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At Arm, we want to build extraordinary teams. If you need an adjustment or an accommodation during the recruitment process, please email [email protected]. To note, by sending us the requested information, you consent to its use by Arm to arrange for appropriate accommodations. All accommodation or adjustment requests will be treated with confidentiality, and information concerning these requests will only be disclosed to the extent necessary to provide the accommodation. Although this is not an exhaustive list, examples of support include breaks between interviews, having documents read aloud, or office accessibility. Please email us about anything we can do to accommodate you during the recruitment process.
Hybrid Working
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Arm’s approach to hybrid working is designed to create a working environment that supports both high performance and personal wellbeing. We believe in bringing people together face to face to enable us to work at pace, whilst recognizing the value of flexibility. Within that framework, we empower groups/teams to determine their own hybrid working patterns, depending on the work and the team’s needs. Details of what this means for each role will be shared upon application. In some cases, the flexibility we can offer is limited by local legal, regulatory, tax, or other considerations, and where this is the case, we will collaborate with you to find the best solution. Please talk to us to find out more about what this could look like for you.
Equal Opportunities
-----------------------
Arm is an equal opportunity employer, committed to providing an environment of mutual respect where equal opportunities are available to all applicants and colleagues. We are a diverse organization of dedicated and innovative individuals, and don’t discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Salary Context
This $207K-$281K range is above the 75th percentile for AI Product Manager roles in our dataset (median: $185K across 167 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 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At Arm, 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 in Demand for This Role
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 $217,100 based on 471 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($244K) sits 13% above the category median. Disclosed range: $207K to $281K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Arm AI Hiring
Arm has 1 open AI role right now. They're hiring across AI Product Manager. Based in Austin, TX, US. Compensation range: $281K - $281K.
Location Context
AI roles in Austin pay a median of $214,343 across 143 tracked positions.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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