Microsoft AI is a customer-first organization focused on building AI-powered products that help customers and businesses achieve more in an evolving technology landscape. As AI reshapes how people discover information, engage with services, and conduct business, we need product leaders who can navigate ambiguity, bring clarity to complex challenges, and drive meaningful customer and business impact.
As a member of the Microsoft AI Monetization Platform Trust & Safety team, you will play a critical role in ensuring that our products and platforms remain safe, trustworthy, and effective. You will work on some of the most important challenges facing modern digital ecosystems, including trust and safety, fraud and abuse prevention, risk management, operational excellence, quality systems, automation, and AI-driven decision making. In this role, you will partner closely with Engineering, Data Science, Research, Operations, Policy, Risk, and Business stakeholders to define and deliver scalable solutions that protect users, customers, advertisers, and the broader ecosystem while enabling sustainable business growth. You will help shape how Trust & Safety systems operate, how risk is measured and managed, and how emerging technologies such as AI and agentic systems can be leveraged to improve outcomes at scale.
Has experience in Trust & Safety, Integrity, Fraud Prevention, Abuse Prevention, Risk Management, Policy, Security, Compliance, Operations, Analytics, or related domains.
Demonstrates strong ownership and a bias for action, consistently driving measurable impact through data-driven decision making.
Operates effectively across complex cross-functional environments, balancing customer, business, operational, policy, and technical considerations.
Excels at translating ambiguous problems into scalable solutions and influencing outcomes across diverse stakeholder groups.
Possesses strong analytical capabilities and uses data to identify opportunities, risks, operational improvements, and investment priorities.
Is energized by fast-moving environments and enjoys solving complex ecosystem-wide challenges at scale.
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You will work within the Microsoft AI (MAI) organization, powering AI-first experiences across products including Copilot, Bing, Edge, MSN, and future AI-driven services. MAI brings together Product, Engineering, Research, Design, and Go-To-Market teams to deliver innovative solutions at global scale. As part of a highly collaborative, cross-functional team, you will partner with engineers, designers, researchers, operators, analysts, marketers, and business leaders to build impactful customer experiences. We operate with a strong sense of ownership, customer obsession, and data-driven decision making in a rapidly evolving AI landscape.
As AI transforms the digital ecosystem, this role offers a unique opportunity to help define how trust, safety, quality, and operational excellence evolve in an increasingly agentic world.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. Our employees embrace a growth mindset, innovate to empower others, collaborate to realize shared goals, and contribute to a culture grounded in respect, integrity, accountability, and inclusion. This role is ideal for a builder who thrives in ambiguity, enjoys rapidly turning ideas into prototypes and scalable solutions, and is passionate about leveraging data, automation, AI, and operational excellence to improve Trust & Safety outcomes at global scale.
Responsibilities
Partner with Engineering, Data Science, Operations, Policy, Risk, and Security teams to proactively identify vulnerabilities, abuse vectors, and emerging threats across Trust & Safety systems.
Design and execute adversarial testing programs that challenge detection models, enforcement systems, review processes, and operational workflows.
Simulate real-world attacker behaviors, fraud tactics, prompt attacks, evasion techniques, policy circumvention attempts, and abuse patterns to uncover system weaknesses.
Identify, document, and prioritize vulnerabilities, failure modes, blind spots, and emerging risks, driving mitigation strategies with partner teams.
Create adversarial datasets, benchmark sets, attack corpora, and test scenarios to evaluate system robustness, reliability, and resilience.
Perform hands-on labeling, content review, evaluation, and adjudication activities as needed to establish ground truth, characterize new attack patterns, validate vulnerabilities, and improve model performance.
Generate actionable insights from investigations, attack simulations, labeling exercises, evaluation programs, and operational datasets to identify emerging trends and evolving threat patterns.
Partner with Engineering and Data Science teams to improve model performance through adversarial testing, error analysis, red-team evaluations, feedback loops, and continuous learning mechanisms.
Define red-teaming methodologies, attack taxonomies, threat models, and evaluation frameworks to systematically assess Trust & Safety defenses.
Monitor external abuse trends, fraud ecosystems, industry developments, and emerging AI-powered attack techniques relevant to digital advertising and online platforms.
Design experimentation and validation frameworks to assess the effectiveness of new defenses, controls, models, and enforcement mechanisms.
Drive cross-functional initiatives from threat discovery through mitigation while balancing customer experience, operational efficiency, safety, and business objectives.
Communicate technical findings, attack patterns, risk assessments, and strategic recommendations to technical and non-technical stakeholders.
Embody Microsoft’s Culture and Values.
Qualifications
Bachelor's Degree in Business, Public Policy, Communications, Operations, Economics, Psychology, Social Sciences, Data Science, Analytics, Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
3+ years of experience in Trust & Safety, Risk Management, Fraud Prevention, Abuse Prevention, Integrity Systems, Security, Threat Intelligence, Quality Operations, Product Management, Program Management, Analytics, Marketplace Integrity, or related domains.
Experience identifying vulnerabilities, abuse patterns, operational risks, adversarial behaviors, quality gaps, or system weaknesses using data-driven approaches.
Strong analytical and problem-solving skills with experience investigating complex issues, generating insights, and driving risk mitigation initiatives.
Experience working across cross-functional teams including Engineering, Data Science, Operations, Policy, Risk, and Business stakeholders.
Demonstrated ability to translate ambiguous threats, risks, or quality issues into actionable recommendations, evaluation frameworks, or operational improvements.
Familiarity with AI/ML-powered systems and the role of adversarial testing, human review, labeling, evaluation, and feedback loops in improving model quality and safety outcomes.
Experience evaluating products, models, workflows, or operational processes using experimentation, metrics, audits, data analysis, or structured investigations.
Strong communication, stakeholder management, and influencing skills.
Preferred Qualifications:
Experience working in large-scale Trust & Safety, Marketplace Integrity, Fraud Prevention, Online Safety, Security, Risk Management, Compliance, or Content Moderation environments.
Familiarity with Generative AI, Agentic AI, Large Language Models (LLMs), jailbreak techniques, prompt attacks, model evasion techniques, and adversarial AI evaluation methodologies.
Hands-on experience performing labeling, evaluation, adjudication, calibration reviews, abuse investigations, or content assessments to create high-quality adversarial and ground-truth datasets.
Experience generating actionable insights from large-scale investigation, evaluation, risk, quality, enforcement, or operational datasets and translating findings into model, product, or policy improvements.
Working knowledge of SQL, Power BI, Python, or similar analytics and reporting tools.
Experience partnering with Engineering and Data Science teams to improve AI/ML systems through red-teaming, evaluation design, labeling strategies, error analysis, experimentation, and feedback-loop mechanisms.
Demonstrated curiosity, investigative mindset, and ability to identify emerging risks before they become material business or ecosystem issues.
Proven ability to thrive in fast-paced, ambiguous environments while driving measurable customer, quality, safety, and business impact.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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