Jobs
Overview
Join us at Microsoft AI as we build the next-generation Agentic Platform, enabling intelligent autonomous agents that reason, collaborate, and dynamically orchestrate tasks across distributed systems and data at global scale. Our team transforms cutting-edge AI into reliable, production-grade platform. If you are passionate about building large-scale distributed systems and modern web experiences while working with a collaborative team solving complex engineering challenges, we would love to hear from you.
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- Design, develop, and operate large-scale distributed systems that power our agentic platform.
- Build highly scalable and reliable backend services that enable autonomous agents to orchestrate tasks across services, tools, and data.
- Develop modern frontend experiences and tools that enable developers and users to interact with agentic systems and platform capabilities.
- Contribute to full-stack development, including backend services, APIs, and frontend applications.
- Contribute to the architecture and design of cloud-native platform components including compute orchestration, storage systems, and service infrastructure.
- Optimize data access patterns, compute workflows, and system performance to meet strict reliability and latency requirements across online and offline workloads.
- Collaborate closely with AI researchers, infrastructure engineers, product managers, and designers to translate research innovations into production-ready systems.
- Ensure platform services meet high standards of reliability, observability, security, and operational excellence.
- Participate in code reviews, system design discussions, and engineering best practices to improve overall system quality.
- Provide technical mentorship and contribute to a culture of collaboration, innovation, and continuous improvement.
Qualifications:
Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or PythonOR equivalent experience.
Preferred Qualifications:
- Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or PythonOR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
- Extensive experience designing and operating large-scale distributed systems in production environments.
- Experience building services on Microsoft Azure or other major cloud platforms.
- Experience with Kubernetes, containers, and microservices-based architectures.
- Experience designing systems involving distributed data platforms, SQL databases, and high-scale storage systems.
- Solid experience building modern frontend applications using React, REST APIs, and component-based UI architectures.
- Familiarity with full-stack development patterns and integrating frontend systems with backend platform services.
- Experience improving system reliability, scalability, and performance at cloud scale.
- Solid collaboration skills and experience working across engineering, infrastructure, research, and product teams.
#MicrosoftAI
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 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, read more about requesting accommodations.
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About Microsoft
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3.8
5 reviews
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Compensation
4.3
Culture
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Career
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Management
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Pros
Excellent compensation and benefits package
Four-day workweek with improved work-life balance
Supportive managers and teams
Cons
High-pressure environment causing anxiety
Unprofessional interview processes
Limited creative work opportunities
Salary Ranges
5,571 data points
Junior/L3
Mid/L4
Junior/L3 · Advertising Client Success
2 reports
$163,358
total / year
Base
$141,875
Stock
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Bonus
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$163,358
$163,358
Interview Experience
7 interviews
Difficulty
3.7
/ 5
Duration
14-28 weeks
Offer Rate
14%
Experience
Positive 14%
Neutral 29%
Negative 57%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview
5
Onsite/Virtual Interviews
6
Final Round
7
Offer
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