Overview

Windows is one of the largest codebases in the world, running on more than a billion devices. The Windows Engineering System team is the backbone that enables Windows engineers to design, build, validate, and ship at scale—securely and with high quality. Windows, and the industry at large, are entering a new era of AI-discovered vulnerabilities. The pace of vulnerability discovery is changing, with advances in AI making it possible to find more issues, faster, across more code, and new mechanisms that can accelerate both discovery and analysis. The fastest way to reduce customer exposure is to find issues before attackers can use them. As Windows leadership has announced publicly, Windows is expanding its ability across the platform to find issues earlier, accelerate the engineering work to fix them, strengthen validation, and deliver timely, high-quality updates that keep customers protected. Meeting this reality means building autonomous systems that scale vulnerability discovery, proof, and submission to AI-scale volume.

Windows Engineering Systems owns running and operating service infrastructure to tackle this problem called autonomous “autopilots.” The “Hunter” autopilot loop runs Microsoft Security’s multi-model scanning harness (MDASH) over Windows source and proves candidate vulnerabilities exploitable on real VMs, so only the highest-confidence findings ever reach engineers. Windows runs on over a billion devices, so running this at Windows scale has meant standing up dedicated cloud infrastructure for scanning and proving. As a Principal Software Engineer, you will help scale that backbone to the next order of magnitude to keep pace with AI-scale discovery, driving systems engineering at the scale of one of the world’s largest codebases.

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

Why this role exists

As AI-powered discovery expands to more code and more scenarios, the scanning-and-proving infrastructure behind it must grow by an order of magnitude: more throughput, broader coverage, and production-grade reliability. That growth lands squarely on backend compute and orchestration. This role owns the distributed backbone that makes vulnerability discovery and proof run reliably and cost-effectively at Windows scale.

What you'll own

AI Evals & Benchmarks: Building AI evals and benchmarks to ensure that the system stays healthy and does not regress across multiple scenarios.
Throughput & Reliability: Scaling the pipeline by an order of magnitude and improve reliability.
Compute, Capacity & Orchestration: Managing compute and AI infra at Windows-wide scale; smoothing capacity spikes across model-hosting backends; managing queuing/scheduling and pool prioritization infrastructure
Cost & Efficiency: Driving billing/consumption estimation and cost-of-goods modeling.

Who you are

6+ years building large-scale distributed systems / service backends (queuing, scheduling,
autoscaling, multi-tenant compute).
Deep experience with capacity planning, throughput/latency SLAs, and cost-of-goods on cloud infrastructure (Azure preferred).
Track record owning architecture of a complex, ambiguous system end to end, and
mentoring senior engineers.
Comfortable negotiating and holding a hard dependency line with partner teams

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 Python,
- OR equivalent experience.

Preferred Qualifications:

Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience,
- OR Bachelor's Degree AND 12+ years technical engineering experience,
- OR equivalent experience.
Experience building or operating AI agent / LLM-based systems at production scale.
Hands-on experience with Azure DevOps (ADO) pipelines and CI/CD automation.
Deep experience with Microsoft Azure cloud infrastructure (compute, capacity planning, cost-of-goods).
Comfortable working with C# and Microsoft technologies, including hands-on experience with Microsoft Copilot CLI, Azure DevOps (ADO) pipelines and CI/CD automation.
Demonstrated experience designing and operating large-scale distributed systems or cloud service backends (orchestration, scheduling, autoscaling, or multi-tenant compute).

#Windows

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $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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