AI systems are rapidly becoming more capable, autonomous, interconnected, and embedded in products people depend on. As models gain memory, tools, identity, and the ability to act across systems, new risks can emerge through long-running interactions, coordinated agents, and behavior spanning accounts, products, and time—often beyond what any individual product or runtime control can see. Within the Artificial Generative Intelligence Security (AeGIS) team, the AI Safety Platform (AISP) is Microsoft's shared AI observability, detection, investigation, and hunting platform built for this new landscape. We connect fragmented activity across Microsoft's AI estate and turn it into reusable detections, investigation-ready evidence, threat intelligence, and customer protection.
We are looking for a hands-on Principal Software Engineer for a deeply consequential technical builder role at the intersection of cybersecurity and generative AI. You will lead through code and ideas: defining detailed architectures, building large-scale data and detection systems, working through security and privacy reviews, and partnering with cross-company leaders, product engineers, applied scientists, threat hunters, and incident responders from early exploration through production operation. The ideal candidate is deeply curious about how AI systems work, how they break, and how to make them safer and more robust.
We are a mission-driven, collaborative team that leans into uncertainty, learns quickly, and builds on one another's ideas. Our people bring a wide range of backgrounds, disciplines, and life experiences, and we believe that diversity makes both our engineering and our judgment stronger. We want someone energized by technically fascinating problems and by the responsibility to protect users at the scale of some of the world's most widely deployed AI platforms.
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
- Lead the design and implementation of shared platform capabilities: guide architecture and technology decisions, establish reusable engineering patterns, write critical production code, and unblock complex technical work across teams.
- Build and evolve company-wide AI observability and monitoring systems that enable attack reconstruction, automated detection, evaluation, threat hunting, and investigation, using modern agentic development tools and AI-assisted coding workflows to prototype, evaluate, and iterate rapidly.
- Design detection infrastructure for attack signatures, pattern matching, behavioral anomaly detection, model-assisted analysis, and emerging research techniques. Apply emerging AI security research to detection, evaluation, observability, and safer implementation patterns.
- Build and operate large-scale distributed data processing systems using technologies such as Spark, Kusto, data lakes, and batch and streaming platforms. Develop high-volume data integrations and correlation pipelines that turn multi-source telemetry into investigation-ready evidence, threat intelligence, trends, and reporting.
- Drive technical partner conversations and security and privacy architecture reviews, resolve detailed design constraints, and work with teams through integration and implementation.
- Review designs and code, mentor engineers and scientists, and raise the technical bar across teams.
Qualifications
Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience, including significant ownership of distributed data, platform, or security products with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
- 2+ years of experience working on modern AI systems, such as copilots, agent-based products, LLM applications, agent orchestration and tool use, embeddings, vector databases, retrieval-augmented generation, or evaluations.
- 2+ years of experience big data engineering, such as Spark, Kusto, data lakes, batch and streaming pipelines, data quality, performance tuning, and cost and reliability trade-offs.
- Demonstrated success designing and delivering complex production systems in ambiguous, cross-functional environments, identifying and addressing security and privacy risks in complex production systems.
- Proven coding, system design, written communication, and technical leadership skills.
- End-to-end technical ownership of complex platforms, data, security, or AI products.
- Hands-on experience with alerting, triage, investigation, threat hunting, or incident response.
- Experience leading security and privacy architecture reviews, applying threat-modeling and secure-by-design principles, and translating review requirements into implementable designs.
- Deep understanding of agentic systems, tools, memory, embeddings, and AI system failure modes.
- Experience with cloud-native distributed platforms, infrastructure as code, CI/CD, and technologies such as Azure Data Factory, Databricks, Kubernetes, or equivalent systems.
- Demonstrated record of mentoring and influencing engineers, researchers, product leaders, and partner organizations without direct authority.
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.
Skills Required
- Bachelor's degree in Computer Science or a related technical field, or equivalent experience
- 6+ years of technical engineering experience
- Significant ownership of distributed data, platform, or security products
- Professional coding experience in languages including C, C++, C#, Java, JavaScript, or Python
- Ability to pass the Microsoft background and Microsoft Cloud background checks upon hire or transfer and every two years thereafter
- 2+ years working on modern AI systems, such as copilots, agent-based products, LLM applications, embeddings, vector databases, retrieval-augmented generation, or evaluations
- 2+ years of big data engineering experience with Spark, Kusto, data lakes, batch or streaming pipelines, data quality, performance tuning, and cost and reliability trade-offs
- Experience designing and delivering complex production systems in ambiguous, cross-functional environments
- Experience identifying and addressing security and privacy risks in complex production systems
- Proven coding, system design, written communication, and technical leadership skills
- End-to-end technical ownership of complex platforms, data, security, or AI products
- Hands-on experience with alerting, triage, investigation, threat hunting, or incident response
- Experience leading security and privacy architecture reviews, threat modeling, and secure-by-design practices
- Deep understanding of agentic systems, tools, memory, embeddings, and AI system failure modes
- Experience with cloud-native distributed platforms, infrastructure as code, CI/CD, Azure Data Factory, Databricks, Kubernetes, or equivalent systems
- Experience mentoring and influencing engineers, researchers, product leaders, and partner organizations without direct authority
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.
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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.
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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.
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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.
Microsoft Insights
What We Do
At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. Our mission is grounded in both the world in which we live and the future we strive to create. Today, we live in a mobile-first, cloud-first world, and the transformation we are driving across our businesses is designed to enable Microsoft and our customers to thrive in this world.

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