> Markdown version of [/jobs/ext/4637566-senior-security-software-engineer](https://www.wearedevelopers.com/jobs/ext/4637566-senior-security-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Security Software Engineer

- **Company:** Microsoft
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $119,800 - $234,700
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Microsoft Azure, Microsoft Online Services, C Sharp (Programming Language), C++ (Programming Language), Cloud Computing, Continuous Integration, Python (Programming Language), Machine Learning, Microsoft Software, Node.Js, Software Architecture, Azure Machine Learning, Security Software, Software Engineering, Systems Integration, AI Infrastructure, Network Switches, IT Architecture, Information Technology, Machine Learning Operations, Model Inference
- **Published:** November 8, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-security-software-engineer-new-york-ny--d3a4cf48-1338-472c-aab9-dc66a67e3843

## About the Role

Security Software, Software Engineering, Microsoft Product Family, Cloud Computing, Artificial Intelligence (AI), Threat Modeling, Risk Analysis, Software Engineering, Microsoft Windows Azure, Identify Issues, * Bachelors Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience., + 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 background and Microsoft Cloud background check upon hire/transfer and every two years thereafter., * 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 RL 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 (HPC) 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.

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $160,200 - $261,000 per year.

## Description

* Design, deploy, operate, and troubleshoot secure distributed AI infrastructure in a reliable and scalable way, 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.
 * Work independently from ambiguous research and infrastructure requirements to develop technical designs and production-ready solutions.
 * Partner closely with stakeholders to understand their needs, clarify requirements, and prioritize the highest-impact solutions
 * Drive alignment across engineers, researchers, and partner teams on infrastructure architecture, security and reliability tradeoffs, dependencies, and delivery.
 * Build and improve automation that enables rapid deployment and operation of AI models and supporting infrastructure
 * Build solid relationships with peers through design and code reviews, technical collaboration, and mentoring
 * Embody our Culture and Values