Senior Security Software Engineer

Microsoft • ,

3d • $119,800 - $261,000

About The Position

The Senior Security Software Engineer will join Microsoft’s AI Red Team and build and operate secure, reliable Azure GPU infrastructure for engineers, researchers, and red teamers. The role applies hands-on AI engineering to deploy, operate, and troubleshoot secure distributed training and reinforcement-learning environments that support long-running research workloads. The engineer works with stakeholders to understand needs and translate them into scalable infrastructure capabilities.

The position sits within Microsoft Red Team, which helps the company anticipate emerging threats and strengthen the security of its products, services, and AI systems. The Microsoft AI Red Team identifies risks in Microsoft’s AI systems. Microsoft describes its culture as grounded in a growth mindset, inclusion, collaboration, respect, integrity, and accountability.

Requirements

• Bachelor’s degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
• Meet Microsoft, customer, and/or government security screening requirements, including the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
• Provide citizenship or qualifying status documentation for assessment of eligibility to access export-controlled information; citizenship verification is required for this position.

Nice To Haves

• Experience designing, deploying, and operating cloud infrastructure, including distributed, multi-node, multi-GPU training environments.
• Experience developing software and automation for production systems.
• Experience deploying and operating AI infrastructure in Azure, including GPU-backed compute, networking, model serving, and platforms such as Azure AI Foundry or Azure Machine Learning.
• Experience integrating or operating reinforcement-learning training stacks such as SkyRL, verl, or OpenRLHF and agent environments or sandbox tooling such as Harbor.
• Experience with containers, infrastructure-as-code, CI/CD, monitoring, and observability.
• Experience diagnosing GPU, interconnect, or performance issues in GPU or high-performance computing infrastructure.
• Proficiency writing clean, efficient, and maintainable Python code.
• Understanding of LLM inference, model deployment, and the performance, capacity, and reliability requirements of large AI models.
• Experience driving technical projects from ambiguous requirements to production, including stakeholder alignment and architectural decisions.
• Experience in cybersecurity, AI security, or red teaming.

Responsibilities

• Design, deploy, operate, and troubleshoot secure distributed AI infrastructure, including multi-node, multi-GPU training and reinforcement-learning environments.
• Build fleet-level automation and infrastructure-as-code for remediation, repeatable configuration, and drift detection.
• Turn recurring findings into durable engineering fixes that prevent recurrence.
• Independently develop technical designs and production-ready solutions from ambiguous research and infrastructure requirements.
• Partner with stakeholders to understand needs, clarify requirements, and prioritize high-impact solutions.
• Drive alignment across engineers, researchers, and partner teams on infrastructure architecture, security and reliability tradeoffs, dependencies, and delivery.
• Build and improve automation for rapid deployment and operation of AI models and supporting infrastructure.
• Build relationships with peers through design and code reviews, technical collaboration, and mentoring.
• Embody Microsoft’s Culture and Values.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior