Senior Software Engineer

Reposted 17 Days Ago
Be an Early Applicant
Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Design and develop crash-dump, debugging, diagnostic, telemetry, and post-mortem analysis tools for GPU and AI accelerator platforms. Work across host software, drivers, firmware, hardware, and cloud infrastructure to diagnose failures, improve reliability, automate root-cause analysis, and support multiple accelerator architectures. Collaborate cross-functionally, participate in technical reviews, improve engineering practices, and mentor engineers while applying AI-assisted development workflows.
Summary Generated by Built In
Overview
Microsoft’s AI infrastructure is evolving rapidly to support the next generation of large-scale AI training and inference. The AI Frameworks (AIFx) Networking & Systems Tools (NeST) organisation develops foundational system software that enables Microsoft’s Maia accelerator platforms across pre-silicon development, hardware bring-up, cloud integration and production cloud infrastructure that enables AI accelerators to operate reliably and efficiently at cloud scale.
 
Within NeST, the India Development Centre is building end-to-end engineering competency across the Maia system software stack. Our work spans the boundary between distributed cloud systems and low-level accelerator software, including control-plane services, host and device management software, accelerator virtualisation, Kubernetes-based infrastructure, Developer/Debugger Infrastructure tools, hardware lifecycle management, reliability, telemetry and diagnostics.
 
We are looking for a Senior Software Engineer to design and build debugging and diagnostic capabilities for GPU and AI accelerator platforms. You will develop tools that help engineers diagnose complex hardware and software failures, accelerate root-cause analysis and improve the reliability and serviceability of AI 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 crash dump collection, processing and analysis tools for GPU and AI accelerator platforms.
• Build hardware debugging tools for device inspection, failure analysis and low-level platform diagnostics.
• Develop diagnostic capabilities spanning host software, device drivers, firmware and accelerator hardware.
• Build tools for post-mortem debugging, failure triage and root-cause analysis.
• Develop scalable mechanisms for collecting and analysing logs, traces, telemetry and diagnostic data.
• Design extensible APIs and tooling that can support multiple hardware generations and accelerator architectures.
• Improve automation around failure detection, debugging and diagnostics to reduce engineering effort during complex system investigations.
• Work with hardware, firmware, driver, platform and cloud infrastructure teams to diagnose cross-layer issues.
• Drive improvements in tooling quality, reliability, testability, performance and developer experience.
• Participate in architecture and design reviews, contribute to engineering practices and mentor other engineers.
• Apply AI-assisted engineering practices across design, coding, testing, debugging and documentation to improve engineering velocity and software quality.
• Leverage AI-assisted workflows to accelerate crash analysis, code comprehension, failure triage, root-cause investigation and test development, while validating results through sound engineering practices.
• Identify opportunities to use AI to automate repetitive diagnostic and debugging workflows, reducing engineering effort and accelerating problem resolution.
• Use AI-assisted learning to develop deeper competency across systems software, computer architecture, firmware, drivers and AI accelerator infrastructure.
• Develop and share reusable AI-assisted engineering practices that improve team productivity, technical learning and domain competency.
 

Qualifications

Required Qualifications: 

• Bachelor’s Degree in Computer Science, Computer Engineering, Electrical Engineering or related technical discipline, or equivalent experience with 8+ years of industry relevant experience.
• Software development skills in C, C++, C#, Rust, Python or similar languages.
• Experience developing systems software, debugging tools, diagnostic software or developer tools.
• Understanding of operating systems, computer architecture, memory management, concurrency and low-level software concepts.
• Debugging and problem-solving skills, including diagnosing complex software or hardware/software interaction issues.
• Experience developing reliable, maintainable and testable production software.
• Design and cross-team collaboration skills.
• Ability to use AI-assisted engineering tools and workflows to improve development, debugging, testing, technical learning and engineering effectiveness.
 
Preferred Qualifications: 
• Experience developing crash dump, debugger, tracing, profiling or diagnostic tools.
• Experience with GPU, AI accelerator or heterogeneous compute systems.
• Knowledge of PCIe, device interfaces, memory-mapped I/O or hardware/firmware interaction.
• Experience with Linux systems programming, kernel interfaces or device drivers.
• Familiarity with JTAG, OpenOCD or similar hardware debugging technologies.
• Experience with telemetry, tracing, logging, observability and post-mortem analysis.
• Understanding of firmware, embedded systems or SoC architectures.
• Experience building developer tools that operate across different hardware generations or platforms.
• Experience using AI-assisted techniques for code analysis, debugging, test generation, failure investigation or engineering automation.
• Ability to leverage AI-assisted learning to quickly develop expertise across new hardware architectures, firmware, drivers and diagnostic technologie
 
 
#AIINFRA

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.

Skills Required

  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline, or equivalent experience with 8+ years of relevant industry experience
  • Software development experience in C, C++, C#, Rust, Python, or similar languages
  • Experience developing systems software, debugging tools, diagnostic software, or developer tools
  • Understanding of operating systems, computer architecture, memory management, concurrency, and low-level software concepts
  • Ability to diagnose complex software or hardware-software interaction issues
  • Experience developing reliable, maintainable, and testable production software
  • Design and cross-team collaboration skills
  • Ability to use AI-assisted engineering tools and workflows for development, debugging, testing, technical learning, and engineering effectiveness
  • Experience developing crash dump, debugger, tracing, profiling, or diagnostic tools
  • Experience with GPU, AI accelerator, or heterogeneous compute systems
  • Knowledge of PCIe, device interfaces, memory-mapped I/O, or hardware-firmware interaction
  • Experience with Linux systems programming, kernel interfaces, or device drivers
  • Familiarity with JTAG, OpenOCD, or similar hardware debugging technologies
  • Experience with telemetry, tracing, logging, observability, and post-mortem analysis
  • Understanding of firmware, embedded systems, or SoC architectures
  • Experience building developer tools across different hardware generations or platforms
  • Experience using AI-assisted techniques for code analysis, debugging, test generation, failure investigation, or engineering automation
  • Ability to use AI-assisted learning to develop expertise across new hardware architectures, firmware, drivers, and diagnostic technologies

Microsoft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.

  • Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
  • Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
  • Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.

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The Company
HQ: Redmond, WA
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Year Founded: 1975

What We Do

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