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Overview: ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future.
Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career. Responsibilities: THE ROLE:
In our Business Development, Enterprise AI Channel role, you will drive the development and execution of AMD’s enterprise AI go-to-market strategy across channel partners, independent software vendors, OEMs, systems integrators, and enterprise customers.
This role is responsible for building the partnerships, solutions, sales motions, and market programs required to accelerate adoption of AMD Instinct™ accelerators, AMD EPYC™ processors, ROCm™ software, and the broader AMD enterprise AI portfolio.
In the Business Development, Enterprise AI Channel role you will operate as a strategic advisor to partners and customers, helping them translate AMD technology into differentiated AI solutions and measurable business outcomes. The role combines business development, ecosystem strategy, partner enablement, solution development, and consultative selling.
The successful candidate will identify market opportunities, recruit and develop strategic partners, establish joint business plans, create repeatable solution plays, influence enterprise opportunities, and coordinate the resources required to move AMD-based AI solutions from initial interest to production adoption.
In this highly collaborative role, you will work with AMD sales, engineering, product management, product marketing, developer relations, finance, legal, operations, and executive leadership. THE PERSON:
The ideal candidate is an experienced business development leader who understands enterprise AI, partner-led routes to market, and complex technology sales.
You can build relationships with channel executives, ISV leaders, enterprise decision-makers, sellers, consultants, and technical teams. You are comfortable developing a market strategy, negotiating a joint business plan, advising a customer on AI adoption, and helping sales teams advance strategic opportunities.
You take a consultative approach to business development, connecting customer requirements and market opportunities with AMD products, software, partners, and technical resources. You can translate complex technology into compelling business value while maintaining the commercial focus required to create pipeline, accelerate opportunities, and grow revenue.
You possess excellent interpersonal, communication, negotiation, and presentation skills. You can work independently and across a highly matrixed organization while managing multiple partners, programs, and priorities. KEY RESPONSIBILITIES:
- Develop and execute enterprise AI business development and go-to-market strategies with channel partners, ISVs, distributors, and enterprise customers.
- Establish and expand strategic relationships with partner executives, business leaders, sales organizations, solution practices, and technical stakeholders.
- Recruit and develop partners that can build, sell, deploy, and support enterprise AI solutions based on AMD technology.
- Create joint business plans covering target markets, priority accounts, pipeline objectives, solution development, enablement, marketing investments, and execution milestones.
- Build differentiated partner solution offerings around AMD Instinct accelerators, AMD EPYC processors, ROCm software, and AMD-supported enterprise AI solutions.
- Identify high-value enterprise AI workloads and translate them into repeatable industry, use-case, and workload-specific sales plays.
- Drive account mapping, opportunity identification, co-selling, and executive alignment across AMD, channel partners, ISVs, OEMs, and enterprise customers.
- Build and maintain a qualified pipeline of partner-led enterprise AI opportunities.
- Influence strategic opportunities from initial discovery and qualification through evaluation, commercial alignment, deployment, and production expansion.
- Develop business cases, value propositions, TCO models, ROI analyses, executive presentations, and competitive positioning supporting AMD-based AI investments.
- Articulate AMD business value across AI economics, cost per token, infrastructure utilization, performance per watt, deployment flexibility, workload portability, and supply-chain diversification.
- Serve as a strategic business advisor to partners and enterprise customers evaluating AI use cases, infrastructure strategies, operating models, and deployment options.
- Develop partner enablement programs for executives, sellers, consultants, solution architects, and delivery organizations.
- Create sales plays, discovery guides, customer presentations, solution briefs, competitive materials, objection-handling guidance, and other partner-ready GTM assets.
- Deliver executive briefings, partner workshops, business discovery sessions, sales training, and solution strategy engagements.
- Work with ISVs to prioritize software enablement, validate strategic workloads, develop joint solutions, and establish commercial routes to market.
- Build the business case for ISV investment in AMD, including customer access, joint selling, solution integration, marketing, and ecosystem expansion.
- Coordinate with AMD technical subject matter experts to ensure proposed solutions are technically credible, supportable, and aligned with customer requirements.
- Support proof-of-concept programs by defining business objectives, success criteria, executive sponsorship, stakeholder alignment, and the path to production.
- Identify and resolve barriers to AMD adoption related to software compatibility, solution validation, partner readiness, services, support, financing, skills, and organizational requirements.
- Monitor competitive platforms, enterprise buying behavior, AI workload trends, partner capabilities, and emerging market opportunities.
- Track pipeline creation, revenue influence, partner readiness, solution development, workload validation, opportunity progression, and program effectiveness.
- Conduct regular business reviews with partners and AMD leadership, providing recommendations on investment priorities, execution risks, and growth opportunities.
- Represent AMD at customer meetings, partner events, executive briefings, industry conferences, and ecosystem forums.
PREFERRED EXPERIENCE:
- Proven business development, alliance management, channel development, ecosystem strategy, enterprise sales, or go-to-market experience.
- Experience developing business with value-added resellers, systems integrators, OEMs, distributors, managed service providers, cloud providers, or ISVs.
- Demonstrated success creating joint business plans, partner programs, solution sales motions, and measurable pipeline.
- Experience influencing complex enterprise technology opportunities involving multiple vendors, partners, decision-makers, and technical stakeholders.
- Understanding of enterprise AI adoption, including use-case discovery, infrastructure selection, model development, inference, deployment, governance, operations, and scaling.
- Knowledge of AMD Instinct accelerators, AMD EPYC processors, ROCm software, open-source AI frameworks, and the broader AI ecosystem is strongly preferred.
- Experience developing business cases, TCO and ROI analyses, market assessments, account strategies, and executive recommendations.
- Ability to translate technical capabilities into customer value, commercial opportunities, and partner differentiation.
- Understanding of competitive AI platforms, enterprise procurement, channel economics, and partner-led routes to market.
- Strong executive communication, negotiation, presentation, and relationship-management skills.
- Ability to lead through influence across matrixed and geographically distributed organizations.
- Experience in financial services, healthcare, life sciences, manufacturing, energy, telecommunications, retail, or the public sector is preferred.
- Global partner or multinational enterprise experience is a plus.
ACADEMIC CREDENTIALS:
- Bachelor’s degree is highly preferred
- MBA or equivalent experience in business development, technology strategy, or enterprise go-to-market is a plus
This role is not eligible for visa sponsorship.
#LI-MP2
Qualifications: Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.
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 9,653 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At AMD, 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 $220,200 based on 862 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
AMD AI Hiring
AMD has 16 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Product Manager. Positions span Austin, TX, US, Santa Clara, CA, US, San Jose, CA, US.
Location Context
AI roles in Austin pay a median of $207,800 across 271 tracked positions. That's 3% below 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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