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About This Role
Overview
At Small Medium Enterprises and Channel (SME&C), we are leading a high-growth, AI-powered global sales team—one that is deeply connected to our partners and driven by customer success. By uniting our Small Medium Business, Corporate, Strategy, and Partner teams, we are unlocking the largest customer opportunity, backed by the industry’s most significant investments. Leveraging the power of AI and our extensive partner ecosystem, we are redefining how businesses of all sizes adopt technology to drive growth and innovation.
SME&C is more than a sales organization—it’s a culture of innovation, opportunity, and inclusivity. Here, you’ll be part of a diverse, high-performing, and customer-obsessed team where collaboration, connection, and continuous learning fuel everything we do.
If you thrive in a fast-paced, digital-first environment and are eager to make a meaningful impact, explore how SME&C can be the next step in your career. Together, we are shaping the future of business.
As a Partner Solution Sales professional, you will focus on one of Microsoft’s core Solution Areas—AI Business Process within the SMB segment. You will be responsible for driving opportunities from commit to complete (Stages 2–3 of the Microsoft Customer Engagement Methodology, MCEM), operating at scale across a portfolio of high performing CSP (Cloud Solution Providers) partners. This opportunity will allow you to accelerate your career growth, develop deep business acumen, hone your selling skills, and become adept at deal structuring.
You will develop and execute a Partner Solution Area Sales Plan with assigned partners, driving sales through co-sell strategies to achieve quarterly CSA (Clous Solution Area) FRA across the SMB Business. You will lead your partners' commercial performance and drive sustainable sales impact to customers. A key responsibility will be driving Cloud Solution Provider (CSP) revenue through your partner portfolio. Your role will involve acting as a trusted advisor and business leader, developing the business strategy between Microsoft and your partners. You will also enhance your consultative selling skills through MCEM training and actively pursue additional learning opportunities.
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.
Responsibilities Collaboration & Co-Sell
- Collaborates with segment sellers and other internal stakeholders on partner co-selling efforts with portfolio of assigned partners to drive sales pipeline. Develops and executes co-sell strategies that outline activities and expectations that drive Microsoft and partner sales targets. Leads collaboration between internal and external stakeholders to accelerate deal execution, leverage investments, and accelerate sales.
- Tracks cloud solution area co-sell pipeline performance and independently addresses low performance through correction of errors (CoE) efforts. Tracks partner sales capabilities and capacities for sales practice acceleration and growth. Tracks partner incentive utilization and impact on pipeline velocity, and provides recommendations to partner to improve performance. Tracks quarterly forecast to ensure it meets and/or exceeds revenue accountability.
Partner Engagement
- Shares top practices for co-selling with partners and global peers through community forums, contributes to listening circles and contributes to worldwide learning initiatives. Shares market local solution area business momentum insights and corporate research for customer demand.
- Drives the acceleration of cloud solution area sales practice with partners, with a focus on pipeline, go-to-market (GTM) sales and co-sell execution. Drives a predictable cloud solution area rhythm of business (RoB) and addresses performance issues with partners to ensure delivery of cloud solution area partner targets. Independently collaborates with segment sales teams to ensure co-sell performance with partners through joint execution.
- Independently works with prioritized solution area-aligned partners to identify new opportunities with customers. Drives the qualified partner pipeline and progress it through the sales cycle. Ensures partner adoption of investment levers to create opportunities and accelerate deal velocity. responsibility description
Partner Solution Area Sales Plan
- Creates joint solution area sales plans in partnership with prioritized partners in their solution area portfolio relevant to customer segment to address customer needs and drive quarterly revenue accountability. Independently identifies, understands, and evaluates partners' cloud solution area sales practice(s). Contributes to the strategic alignment with organizational units and overall partner business plans to meet sales objectives.
Sales Process & Sales Management
- Independently initiates solution area sales planning with assigned partners and ensures coverage to support targets. Owns a predictable sales pipeline rhythm of business (RoB) with assigned solution area partners. Manages top partner deals and overall partner revenue aligned to solution area.
- Coaches partners on solution play and ensures partners have capability and capacity to deliver the value proposition of the solution play. Facilitates pipeline management meetings and unblocking deals by connecting with Microsoft resources. Develops plans leveraging all of the Microsoft internal resources (e.g., investments, funding) and coaches the partner on how to accelerate their sale process using these tools/resources. Leads business reviews with key partner stakeholders and holds partners accountable for delivery against agreed plan.
- Maintains an understanding of, and upholds Microsoft's current compliance processes.
Other
Embody our Culture and Values
Qualifications Required/minimum qualifications
- Bachelor's Degree AND 4+ years experience in core sales, partner sales, industry or solution selling, marketing, or business development + OR equivalent experience.
Additional or preferred qualifications
- Doctorate AND 3+ years experience in core sales, partner sales, industry or solution selling, marketing, or business development OR Master's Degree AND 6+ years experience in core sales, partner sales, industry or solution selling, marketing, or business development OR Bachelor's Degree AND 8+ years experience in core sales, partner sales, industry or solution selling, marketing, or business development + OR equivalent experience.
- Experience selling Dynamics365 solutions highly preferred
Partner Solution Sales IC4 - The typical base pay range for this role across the U.S. is USD $107,600 - $187,500 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 $145,600 - $205,600 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 $107K-$205K range is below the median for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% 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 Required
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 $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($156K) sits 26% below the category median. Disclosed range: $107K to $205K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Microsoft AI Hiring
Microsoft has 62 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, AI Software Engineer, Research Scientist. Positions span New York, NY, US, Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia, Redmond, WA, US. Compensation range: $128K - $331K.
Location Context
AI roles in Austin pay a median of $209,100 across 306 tracked positions.
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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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