Microsoft has 521 active AI-related job listings. The majority of these roles are focused on agents, representing 37% of the total, followed by application and serving infrastructure. Engineering is the most frequent function, with a significant number of openings, and the United States is the primary hiring country. Frequent tech tags include agent orchestration, model serving, and LLM observability, suggesting a focus on operationalizing AI models. Over the last 30 days, Microsoft has added 280 new AI roles, a 157% increase compared to the previous 30-day period.
Currently tracking 250 active AI roles, down 24% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$331k (avg $195k).
Microsoft currently has 343 active AI-related roles in our index. The most common open titles are: Principal Software Engineer (19), Senior Software Engineer (19), Software Engineer II (8), Principal Applied Scientist (7), Principal Data Scientist (4). Most positions are in Engineering and Research.
Microsoft's active AI hiring is concentrated in: agents (36%), application (21%), serving infrastructure (19%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Microsoft is hiring AI talent in: United States (308 roles), Canada (15 roles), Japan (8 roles), United Kingdom (7 roles).
Job postings at Microsoft most frequently mention: Computer Architecture, Python, Machine Learning, C#, C++.
In the past 30 days, Microsoft has posted 227 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Entry Level Cloud Solution Architect This role focuses on designing and building AI and Agentic solutions for customers using Microsoft's AI platforms like Copilot, Copilot Studio, and Azure AI. The Cloud Solution Architect will work on technical engagements, POCs, and MVPs to accelerate adoption and deliver repeatable AI solutions, acting as a bridge between customer needs and Microsoft's AI offerings. | Agent | 5 |
| Critical Environment Operations This role involves maintaining critical infrastructure in Microsoft's datacenters, focusing on monitoring, inspection, maintenance, troubleshooting, and enforcing safety and security requirements. It also includes developing operational procedures and supporting third-party contractors. | — | 0 |
| Technical Support Engineering Manager |
| — |
| 0 |
| Technical Support Advisory This role focuses on technical readiness and process compliance for frontline support staff, providing subject matter expertise for Microsoft products and services to ensure timely case resolution and drive delivery excellence. It involves case reviews, mentoring engineers, contributing to self-help initiatives, and providing feedback for product and process improvements. | — | 0 |
| Technical Support Engineering Manager This role is a Technical Support Engineering Manager at Microsoft, leading a team of support engineers to resolve complex customer technical issues. The role involves people management, customer relationship management from a support standpoint, ensuring team readiness, driving product/process improvement through feedback and automation, and fostering business integration for a great customer experience. While the company leverages AI extensively and aims to accelerate AI transformation for customers, this specific role focuses on managing the support and resolution of technical issues, not on building or directly deploying AI models or systems. | — | 0 |
| Senior Critical Environment Operations This role is for a Senior Critical Environment Technician responsible for maintaining critical datacenter infrastructure, including monitoring, maintenance, troubleshooting, and ensuring safety and security requirements are met. The role involves developing operating procedures and supporting cloud operations for Microsoft's online services. | — | 0 |
| Entry Level Technical Support Engineer Entry Level Technical Support Engineer at Microsoft, focusing on troubleshooting and resolving customer technical issues using available tools and processes. The role involves identifying defects, escalating issues, providing feedback for product improvement, and collaborating with cross-functional teams. While the role is within an organization that leverages AI, it does not involve building or directly working with AI models or systems. | — | 0 |