The Azure Core NIC team designs, develops, and deploys multiple generations of Smart Network Interface Cards (SmartNICs) that deliver advanced hardware offloads, including RDMA and other high-performance networking capabilities. As Azure's networking requirements continue to grow, the team is expanding to support the increasing demand for high bandwidth, ultra-low latency, high availability, and efficient compute utilization across both AI workloads and general-purpose cloud infrastructure.
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
- Design and develop software for Azure SmartNIC platforms and networking offload technologies.
- Improve performance, scalability, and reliability of networking services supporting Azure compute and storage workloads.
- Work across hardware, firmware, and software boundaries to deliver highly available cloud networking solutions.
- Analyze telemetry and production data to drive reliability and live-site improvements across Azure networking services.
- Partner with silicon, firmware, platform, and service teams to deliver next-generation networking capabilities.
Qualifications
Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C++, C, Rust, or Python
- OR equivalent experience.
Other Requirements:
- Ability 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:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
- Master's Degree in Computer Science or related technical field AND 3+ years technical engineering experience with coding in languages including, but not limited to, C++, C, Rust, or Python
- OR Bachelor's Degree in Computer Science or related technical field AND 5+ years technical engineering experience with coding in languages including, but not limited to, C++, C, Rust, or Python
- OR equivalent experience.
- Experience with the following:
- software design, debugging, performance analysis, and problem-solving in distributed systems or cloud-scale services;
- developing and maintaining automated tests, monitoring, and telemetry for production systems;
- participating in code reviews, design reviews, and engineering best practices;
- networking technologies such as TCP/IP, RDMA, Ethernet, DPDK, SR-IOV, or SmartNIC architectures;
- developing software for Linux-based systems;
- cloud infrastructure, distributed systems, or hyperscale platforms.;
- troubleshooting live-site incidents and improving service reliability;
- working with telemetry, diagnostics, and data-driven operational improvements;
- contributing to large-scale projects involving multiple engineering teams.
- Familiarity with hardware-software interactions, device drivers, firmware, or performance-sensitive systems.
- Ability to independently drive well-defined engineering problems from design through implementation and production deployment.
#azurecorejobs
Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 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 $133,800 - $219,200 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.
Microsoft Mountain View, California, USA Office
1065 La Avenida, Mountain View, CA 94043, Mountain View, United States, 94043
Microsoft Palo Alto, California, USA Office
Palo Alto, United States
Microsoft San Francisco, California, USA Office
835 Market Street, Suite 700, San Francisco, CA 94103, San Francisco, United States, 94103
Microsoft San Jose, California, USA Office
San Jose, United States
Microsoft Sunnyvale, California, USA Office
Sunnyvale, United States
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
