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Overview Microsoft AI is building the next generation of AI\-powered consumer and commercial experiences. As AI reshapes search, shopping, and digital engagement, we are creating agentic commerce experiences that connect users, merchants, brands, and advertisers in new ways.
The AI Commerce Product Marketing team defines how AI\-driven commerce creates customer value and business growth across Copilot, Search, and emerging AI surfaces. We partner with Product, Engineering, Design, Research, Business Development, Sales, and Marketing to shape strategy, drive adoption, and accelerate category leadership.
The AI Commerce Product Marketing team is seeking a Director of Product Marketing, AI Commerce to lead AI Commerce initiatives across emerging shopping, merchant, and transactional experiences. You’ll shape the future of AI\-powered commerce, enabling businesses to deliver seamless product discovery, intelligent recommendations, and frictionless purchasing across digital touchpoints.
As a Director of Product Marketing, you will use strategic thinking, product intuition, storytelling, market insight, and operational skills to build and scale innovative products in commerce, marketplaces, search, AI, or adjacent domains. You will translate complex AI capabilities into clear value propositions and scalable go\-to\-market strategies. You’ll partner extensively with Product and Engineering to influence roadmap, identify growth opportunities, and define differentiated positioning—thriving in ambiguous, fast\-moving environments and influencing across senior leadership, cross\-functional teams, and external partners.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50\- mile commute of a designated Microsoft office in the U.S. or 25\-mile commute of a non\-U.S., country\-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities
- Customer \& Market Insight Leadership
+ Lead customer listening strategies to understand evolving shopper, merchant, advertiser, and partner needs, synthesizing research, usage trends, and competitive insights to inform strategy.
+ Anticipate market shifts, competitive threats, and whitespace to define Microsoft’s leadership position, partnering with field and sales teams to influence roadmap prioritization.
- Product Positioning, Messaging \& Narrative
+ Define differentiated positioning and compelling value propositions, translating complex AI capabilities into business impact narratives with proof points and use cases.
+ Drive consistent storytelling and alignment across Product, Communications, Sales, and Marketing, shaping the broader category narrative for AI\-enabled commerce.
- Go\-to\-Market Leadership \& Enablement
+ Lead end\-to\-end GTM strategies—defining launch readiness, success metrics, segmentation, adoption, and growth plans—and orchestrate integrated release motions across launches, tentpole events, and partner activations.
+ Equip Sales, Business Development, Marketing, and partner teams with positioning, scenarios, and competitive differentiation through scalable enablement materials, playbooks, and training assets.
- Product Strategy \& Cross\-Functional Partnership
+ Serve as a strategic partner to Product and Engineering throughout the product lifecycle, influencing roadmap with customer empathy, market insight, and competitive perspective.
+ Frame business opportunities, prioritize customer problems, and identify monetization pathways for emerging AI commerce scenarios.
+ Collaborate across Microsoft AI, Bing, Copilot, Edge, Advertising, Merchant, and partner ecosystems to align product and GTM priorities.
- Thought Leadership \& Industry Engagement
+ Represent Microsoft’s AI commerce strategy in customer conversations, executive briefings, and industry events. Position Microsoft as a leader in conversational commerce, contributing to executive presentations, blogs, keynotes, and external storytelling.
Qualifications Required Qualifications:
- Master's Degree in Marketing, Computer Science, Business or related field AND 4\+ years experience in product marketing, business planning, or product strategy
+ OR Bachelor's Degree in Marketing, Computer Science, Business or related field AND 6\+ years experience in product marketing, business planning, or product strategy
+ OR equivalent experience.
Preferred Qualifications:
- Master's Degree in Marketing, Computer Science, Business or related field AND 8\+ years in product marketing, business planning, or product strategy
+ OR Bachelor's Degree in Marketing, Computer Science, Business or related field AND 12\+ years experience in product marketing, business planning, or product strategy
+ OR equivalent experience.
- 10\+ years in Product Marketing, Product Management, Strategy, or Business Planning across consumer tech, commerce, AI, or digital platforms.
- Proven experience partnering with Product and Engineering to shape strategy and influence roadmap.
- Experience in positioning, messaging frameworks, and customer\-centric narratives for innovative products.
- Experience leading cross\-functional GTM initiatives across complex organizations.
- Deep understanding of digital commerce, online shopping behaviors, marketplaces, advertising, merchant platforms, or retail tech.
- Experience with written and verbal communication to executive audiences.
- Proven ability to thrive in ambiguous, fast\-moving, collaborative environments.
- Experience using insights, research, experimentation, and analytics to drive decisions.
- Experience with AI products, conversational AI, intelligent agents, recommendation systems, or generative AI.
- Experience in commerce platforms, retail media, search, shopping, fintech, payments, merchant solutions, or ad tech.
- Experience launching new categories or disruptive products.
- Solid understanding of the evolving AI commerce and consumer AI landscape.
\#MicrosoftAI \#ProductMarketing \#PMM \#Marketing \#Commerce \#AgenticCommerce \#MAI
Product Marketing IC5 \- The typical base pay range for this role across the U.S. is USD $130,900\.00 \- $251,900\.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $165,600\.00 \- $272,300\.00 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us\-corporate\-pay
Product Marketing IC5 \- The typical base pay range for this role across the U.S. is USD $130,900 \- $251,900 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $165,600 \- $272,300 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us\-corporate\-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.
Salary Context
This $130K-$272K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 2130 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,133 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Microsoft, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $185,000 based on 13,200 positions with disclosed compensation. Director-level AI roles across all categories have a median of $250,000. This role's midpoint ($201K) sits 9% above the category median. Disclosed range: $130K to $272K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Microsoft AI Hiring
Microsoft has 20 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Research Scientist, Data Scientist. Positions span New York, NY, US, Mountain View, CA, US, San Francisco, CA, US. Compensation range: $151K - $331K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (106) are outnumbered by mid-level (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, 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 Safety roles lead at $274,200 median, while Prompt Engineer roles sit at $140,000. 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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