OverviewThe
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.
Responsibilities- Design and build autonomous red-team systems and agents that discover, exploit, and report vulnerabilities in apps and digital infrastructure at scale.
- Develop agentic workflows leveraging coding agents, RAG, domain knowledge repositories, and tool-integrated agents to accelerate the development, evaluation, and continuous improvement of red-team agents and systems.
- Design reusable data processing frameworks, canonical data models, and data contracts that accommodate evolving red teaming and business require
- Lead architectural decisions across cloud data platforms, distributed compute engines, data lakes, streaming and batch processing, and analytical serving systems, balancing data freshness, correctness, performance, and cost.
- Streamline red-team agent development through automated pipelines for code reviews, failure triage, root-cause analysis, and operational knowledge discovery.
- Establish governance and quality guardrails for red team agents including automated testing, correctness validation, security reviews, and production-readiness checks.
- Embody our culture and corporate values.
QualificationsRequired 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.
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 Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications: - 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.
Data Science 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.
