Principal Applied Scientist

The CogAgents Research team builds intelligent, agentic systems for red teaming—autonomous agents that probe, stress-test, and uncover vulnerabilities in systems at scale. We apply deep learning, large language models, and graph-based models to develop advanced red teaming capabilities for our products, with a focus on agent design, rigorous evaluation, and continuously improving quality and performance.

We are looking for a Principal Applied Scientist to lead the design, evaluation, and productization of red teaming agents. In this role, you will translate complex safety and security challenges into rigorous, data-driven solutions, design agents that identify and exploit weaknesses across systems and applications, and build robust evaluation frameworks that measure attack success, coverage, and overall effectiveness. You will use advanced machine learning techniques to systematically improve agent performance, set a high technical bar, and partner closely with product, engineering, and safety teams to deliver measurable impact. This role requires deep applied machine learning expertise, strong experience in agent design and evaluation, and a focus on turning research into real-world capabilities. We invest in our team's health and culture as key drivers of delivering great outcomes for our customers and partners.

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. 

Required Qualifications: 

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience. 

• 10+ years technical engineering experience with coding in languages including, but not limited to Scala, Python, C#, Java OR equivalent experience.
• 3+ years of experience in deep learning and development of advanced AI systems and agents
• Practical experience applying AI coding assistants, LLMs, and agentic workflows to software development, code modernization, testing, and engineering automation. 
• Experience in RAG, embeddings, semantic search, tool calling, and agent orchestration, with experience implementing appropriate security, correctness, reliability, and human oversight controls.
• Demonstrated understanding of statistical analysis, time-series analytics, anomaly detection, and forecasting.
• Extensive experience in data modeling, analytical data systems, and SQL-based data analysis, including translating ambiguous business requirements into actionable metrics and insights.
• Expertise in architecting, building, and operating production-grade, cloud-native data platforms using Microsoft Fabric, Azure Synapse, Azure AI Foundry, Azure Machine Learning, or equivalent technologies.
• Proven ability to lead cross-team technical initiatives, influence architecture and engineering strategy, navigate ambiguity, and deliver measurable business outcomes.
• Deep proficiency in Apache Spark, Delta Lake, distributed systems, SQL, or large-scale batch and streaming data processing.