Product Manager, AI Safety

About Microsoft AI

Microsoft AI is building AI systems and products that empower people’s lives. Our work is driven by a community of brilliant, interdisciplinary minds working across frontier model development, product engineering, and responsible AI. Within Microsoft AI, the Safety team develops the training methods, evaluations, runtime safeguards, monitoring, and infrastructure needed to make advanced AI systems safer, more reliable, and more useful. Our work spans text, multimodal, and agentic systems and is developed in close partnership with model teams, Production Inference, Security, Responsible AI, Microsoft product organizations, and external partners and customers.

About the Role

We are looking for a product leader to own the interface between Microsoft AI’s safety capabilities and the partners and customers who depend on them. You will turn partner needs, production feedback, regulatory and policy requirements, and emerging safety risks into clear product priorities across Safety Alignment, Multimodal Safety, Production Safety, and Safety Engine. You will also make our safety capabilities easier to understand, adopt, configure, evaluate, and operate in real products.

This PM will own the partner and customer problem space, product requirements, adoption, and cross-team delivery. Success will be measured by whether partners can launch differentiated AI experiences safely and whether their real-world feedback improves our safety roadmap.

Responsibilities

• Serve as the primary product interface for internal Microsoft partners and selected external customers integrating Microsoft AI safety capabilities.
• Develop a deep understanding of partner scenarios, user journeys, deployment constraints, safety risks, and operational pain points through structured discovery and ongoing engagement.
• Translate partner and customer needs into product strategy, requirements, roadmaps, success metrics, and prioritized investments across the safety portfolio.
• Define the product experience for safety services, policies, APIs, evaluations, dashboards, documentation, onboarding, configuration, and support.
• Establish a durable intake and feedback system that connects field signals, incidents, adoption data, and customer evidence to engineering and model-development decisions.
• Drive cross-functional delivery across Safety, model, Production Inference, Security, Responsible AI, policy, legal, support, and product organizations.
• Lead product reviews, dependency management, launch criteria, readiness assessments, and executive communication for safety capabilities and partner launches.
• Define and track outcome-oriented metrics for safety quality, partner adoption, time to integration, operational health, and partner satisfaction.
• Represent partner needs while making principled tradeoffs among safety, capability, user experience, latency, cost, and time to market.
• Create clear narratives and reusable materials that help technical and non-technical stakeholders understand the safety portfolio and make informed decisions.

Required Qualifications

• Experience in product management, technical program leadership, solutions architecture, or a comparable role delivering complex technical products.
• Demonstrated ability to work directly with customers or internal product partners, uncover underlying needs, and translate them into clear technical and product requirements.
• Experience driving products or platforms across multiple engineering, research, policy, operations, and business stakeholders without relying on direct authority.
• Strong technical fluency in machine learning, cloud platforms, developer APIs, data systems, or large-scale online services.
• Ability to define measurable outcomes, make prioritization decisions under uncertainty, and drive execution from discovery through launch and iteration.
• Excellent written and verbal communication skills, including the ability to explain complex technical and safety tradeoffs to executives, engineers, researchers, and customers.

Preferred Qualifications

• Experience with generative AI, large language models, multimodal systems, AI agents, model evaluation, or ML platform products.
• Experience in AI safety, trust and safety, abuse prevention, content moderation, security, privacy, responsible AI, or another risk-sensitive product domain.
• Experience shipping developer-facing platforms, APIs, SDKs, policy systems, or enterprise controls used across multiple products or customer environments.
• Experience partnering with large enterprise customers or strategic product teams on technically complex, high-stakes deployments.
• Familiarity with model post-training, runtime guardrails, safety evaluation, incident response, or production inference systems.
• Experience shaping a product portfolio spanning foundational technology, shared platforms, and end-user product experiences.