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About This Role
Overview
Are you passionate about AI and eager to help transform how the Federal Government delivers on its mission? Join our Cloud & AI Platform Federal team as we help government customers harness the power of cloud and AI to modernize their technology environments, strengthen mission capabilities, and accelerate innovation.
As trusted advisors and subject matter experts, we work alongside Federal customers to modernize infrastructure, optimize operations, and unlock new possibilities with Azure and AI. Whether modernizing environments to be AI-ready, accelerating innovation with AI agents and platforms, empowering developers with AI capabilities, or unifying and modernizing data estates, we help customers build secure, scalable technology solutions that support critical mission outcomes.
In this role, you'll be at the forefront of AI transformation across the Federal Government, helping customers navigate complex technology, security, compliance, and mission requirements while developing strategies that enable them to realize the full potential of cloud and AI. You'll have the opportunity to make a meaningful impact by helping agencies modernize, innovate, and advance some of the nation's most important missions.
As a Cloud & AI Solution Specialist, you will serve as a solution sales expert within our Federal sales organization, working with strategic government customers across a broad Azure portfolio. You will collaborate closely with technical specialists, partners, customer success, engineering, and consulting resources to advance customer priorities, accelerate cloud and AI adoption, grow Azure consumption, and achieve revenue objectives across your assigned accounts.
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 Customer Engagement
- Leads the sales strategy tailored to each customer's security priorities, showcasing Microsoft's dedication to secure, AI-powered transformation and addressing their specific needs within the customer success plan, fostering long-term partnerships through AI-driven insights. Leads partner teams and resources and fosters lasting relationships that activate co-selling strategies and drive partner attach to each opportunity through every stage in the sales lifecycle. Leads partner organization connections (i.e. GPS) that lead to enduring relationships, shared gains, partner health and alignment with execution plans to accelerate customer value realization at scale.
- Assesses and qualifies sales opportunities following sales frameworks and guidelines, ensuring alignment with AI-enhanced sales methodologies and best practices. Leads strategy development for driving and closing complex, high-value opportunities. Partners across organizations (e.g., Account Team Unit [ATU], CSU, ISD, GPS) to drive deal orchestration and ensure seamless handoffs throughout the deal lifecycle. Advances best practices to gain customer trust, secure deals, and strategically mitigate risks to enhance sales activities across the market.
Sales & Pipeline Management
- Strategically analyzes business and emerging opportunities to enhance the customer portfolio and drive customer innovation. Integrates technology (e.g., AI sales agents, automation, Power Platforms) to accelerate growth across assigned domain. Employs comprehensive analysis of propensity, renewal, consumption, and usage data to refine and execute sales strategy. Manages optimization of partners assigned to each account and/or opportunity to ensure seamless handoffs with other teams (e.g., Global Partner Solutions [GPS], Customer Success Unit [CSU], Industry Solutions Delivery [ISD], Partner) throughout the deal lifecycle.
- Leads sales pipeline reviews with internal senior stakeholders to drive forecasting accuracy and meeting sales targets, ensuring the use of AI-powered analytics and forecasting tools to enhance precision. Coaches others on and maintains sales and/or consumption pipeline hygiene to enable tracking to achieve assigned sales metrics using all available tools, resources, and processes Coaches others on and leads to achieve usage and/or consumption pipeline hygiene targets to actively monitor adoption trends, identify opportunities for intervention, enabling customers to realize the value of solutions purchased, drive expansion, and ensure healthier, more predictable renewals.
Sales Strategy
- Leads discussions with senior stakeholders and decision makers for high-value customers to identify, qualify, and accelerate sales opportunities. Serves as a key point of contact for, and partners with internal senior stakeholders within and across organizations to strategically drive customer success. Proactively engages with account teams to align the customer's artificial intelligence (AI) transformation vision with their business priorities and success objectives. Ensures the integration of security principles in customer interactions, opportunity, and pursuits to maintain trust and compliance standards.
- Leads collaborations with others on whitespace analysis and leverages expertise to identify and capitalize on business opportunities and market gaps within the assigned market domain, utilizing AI-driven market intelligence tools to assess trends and insights. Integrates and translates market intelligence, trends, and insights to inform team strategy. Refines and evolves the established market analysis approach to ensure proactive alignment with strategic directives and emerging market trends.
- Synthesizes evaluation of the solution area(s) and market to strategically align sales plays with complex customer priorities and outcomes, incorporating AI-driven predictive analytics to forecast future market needs. Drives cross-functional collaboration to propose and prioritize solutions and strategies that drive customer business objectives. Proactively identifies and addresses gaps, setting the direction for market engagement and sales execution.
- Leads partnerships with others cross-organizationally and guides the development of solutions to enable AI- and cloud-driven transformations for existing and new customers within the region, emphasizing the integration of cutting-edge AI technologies and cloud services. Crafts and refines strategies and engages with customers to distinguish Microsoft’s offerings in the competitive landscape. Acts as a subject matter expert and trusted advisor for customers and drives the adoption of technologies and solutions that align and advance their strategic goals and drive digital transformation.
Qualifications
Required Qualifications
- Bachelor's Degree in Computer Science, Information Technology, Business Administration, Information Security, or related field AND 6+ years experience in technology-related sales or account management + OR equivalent experience.
Other Requirements:Security Clearance Requirements: Candidates must be able to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:* The successful candidate must have an active U.S. Government Top Secret Clearance with access to Sensitive Compartmented Information (SCI) based on a Single Scope Background Investigation (SSBI) with Polygraph. Ability to meet Microsoft, customer and/or government security screening requirements are required pre-offer and post-hire for this role. Failure to maintain or obtain the appropriate U.S. Government clearance and/or customer screening requirements may result in employment action up to and including termination. Clearance Verification: This position requires successful verification of the stated security clearance to meet federal government customer requirements. You will be asked to provide clearance verification information prior to an offer of employment.Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.Citizenship & Citizenship Verification: This position requires verification of U.S citizenship due to citizenship-based legal restrictions. Specifically, this position supports United States federal, state, and/or local United States government agency customers and is subject to certain citizenship-based restrictions where required or permitted by applicable law. To meet this legal requirement, citizenship will be verified via a valid passport, or other approved documents, or verified US government clearance.
Preferred Qualifications
- Master's Degree in Business Administration (i.e., MBA), Information Technology, Information Security, or related field AND 8+ years experience in technology-related sales or account management OR Bachelor's Degree in Computer Science, Information Technology, Business Administration, Information Security, or related field AND 12+ years experience in technology-related sales or account management + OR equivalent experience.
- 6+ years solution or services sales experience.
Solution Area Specialists IC5 - The typical base pay range for this role across the U.S. is USD $133,000 - $222,700 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 $170,300 - $239,800 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 $133K-$239K range is above the median for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% 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 $212,000 based on 11,866 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($186K) sits 12% below the category median. Disclosed range: $133K to $239K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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: $272,250; VP: $235,000.
Microsoft AI Hiring
Microsoft has 65 open AI roles right now. They're hiring across AI/ML Engineer, Research Engineer, AI Software Engineer, AI Product Manager. Positions span TX, US, Washington, DC, US, Mountain View, CA, US. Compensation range: $178K - $331K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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).
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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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