Principal Applied Scientist

Location: Redmond
Posted on: June 23, 2025

Job Description:

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. The Microsoft Security AI Research team develops advanced AI-driven security solutions to protect Microsoft and its customers. Our team combines expertise in large-scale AI, knowledge graphs, and generative models to address evolving security challenges across Microsoft’s complex digital environment. Defending Microsoft’s complex environment provides a unique opportunity to build and evaluate autonomous defense and offense through emerging generative AI capabilities. By leveraging rich security telemetry and operational insights from Microsoft’s Threat Intelligence Center and Red Team, you will have access to a one-of-a-kind environment for innovation at scale. As a Principal Applied Scientist , you will focus on applying advanced graph algorithms and large language models (LLMs) to automate and enhance red-teaming operations. Deep expertise in both graph theory/graph machine learning and large language models is essential for this role. You will be responsible for designing and building AI systems that combine knowledge graphs and LLMs for adversarial simulation, attack path discovery, and threat modeling in a production environment. While cybersecurity experience is preferred, it is not required. 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. Qualifications Required/Minimum Qualifications: Bachelors Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6 years related experience (e.g., statistics, predictive analytics, research) OR Masters Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4 years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3 years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 8 years of professional experience in software development and applied machine learning, including building and deploying production-quality systems. 3 years of hands-on experience with large language models (LLMs), such as prompt engineering, fine-tuning, or developing and deploying LLM-based applications in production. 3 years of hands-on experience with graph theory, graph algorithms, and graph machine learning, including practical work with large-scale graph data in real-world environments. Experience with building, scaling, and deploying graph-based solutions and/or multi-agent frameworks (e.g., AutoGen, LangGraph, crewAI) in cloud environments. Ability to translate advanced graph and LLM research into production-grade software that delivers measurable business or security impact at scale. Other Requirements: 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. Additional or Preferred Qualifications: Proficiency in Python is required, with significant experience developing robust, production-grade AI/ML systems using object-oriented programming. Ph.D. in Computer Science, Machine Learning, Mathematics, or a related field. Experience in cybersecurity domains such as red teaming, adversary emulation, or threat intelligence. Experience combining LLMs with knowledge graphs or graph-based data. Experience with transformer-based models and their application to graph or security data. Familiarity with MLOps, scalable data pipelines, and deploying research in production environments. Experience working with large-scale, heterogeneous datasets and graph-based security telemetry. Strong written and verbal communication skills; ability to present complex technical concepts clearly. Contributions to open-source projects or publications related to graph learning, LLMs, or security. Experience integrating LLMs with knowledge graphs to build high-fidelity adversarial models, enabling more advanced attack simulation and security automation. Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $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. Microsoft will accept applications for the role until June 20, 2025. Responsibilities: Research, design, and develop advanced graph-based and LLM-powered AI systems to automate red-teaming and adversarial simulation. Build and maintain large-scale knowledge graphs and leverage LLMs for representing, reasoning about, and simulating attack paths, threat relationships, and mitigation strategies within Microsoft’s cloud and enterprise environments. Apply state-of-the-art graph algorithms, graph neural networks, and LLM techniques to real-world security data. Collaborate with security researchers, applied scientists, and engineers to design autonomous agents and multi-agent frameworks for security testing and incident response. Integrate data and insights from Microsoft’s Threat Intelligence Center, Red Team, and security telemetry to inform graph and LLM modeling and simulation. Contribute to research prototypes and their operationalization in production systems, with a focus on scalability and robustness. Although this is an individual contributor (IC) role, the Principal Applied Scientist is expected to provide technical leadership, mentor and support staff on technical aspects, and foster a collaborative, team-oriented environment. Develop and deploy state-of-the-art graph AI models to enhance red teaming automation. Embody our culture and values

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