Product Manager, Safety & Security

Cohere is the leading security-first enterprise AI company, dedicated to building cutting-edge AI models and products. The Safety & Security PM role involves bridging AI safety research and product delivery, ensuring that safety features are effectively integrated into the North platform.

Responsibilities:

• Serve as the product bridge between Cohere's safety research teams and North, ensuring that findings from model evaluations, red-teaming, and behavioral research translate into product-level guardrails, controls, and safeguards
• Own the safety product roadmap for Cohere and North, prioritizing features based on research findings, observed misuse patterns, evolving threat vectors, and customer requirements
• Partner with modeling teams to scope and interpret safety evaluations — understanding how Cohere’s underlying models behave across adversarial inputs, edge cases, and high-stakes use cases
• Define and drive evaluation frameworks for assessing how safety properties hold up as models and product capabilities evolve, ensuring regressions surface before they reach customers
• Coordinate the development of guardrails and intervention mechanisms — working across research, engineering, and policy to determine where and how safety controls should be implemented within North's product layer
• Monitor the AI safety research landscape — from prompt injection and jailbreaks to emerging misuse patterns in agentic systems — and ensure North's roadmap reflects what the research is surfacing
• Build processes for scaling safety review as North's surface area grows, including how new features get assessed for safety risk before launch

Requirements:

• 5+ years of product management or research operations experience, with meaningful time working alongside research or ML teams at a technology or AI company
• Technical depth sufficient to engage credibly with safety researchers: you don't need to run evals yourself, but you need to understand what they mean and ask the right questions
• Genuine interest in AI safety and model behavior, including the real-world implications of deploying LLMs in enterprise contexts
• Comfortable operating in ambiguity — safety research surfaces unexpected findings, and this role requires good judgment about what to act on and how fast
• Able to work across researchers, engineers, and product teams and keep everyone aligned without flattening the nuance of what the research is actually saying
• Strong written communicator who can translate complex model behavior findings for non-technical audiences and knows when something needs to be escalated urgently
• Hands-on experience with LLM evaluation, red-teaming, safety benchmarking, or behavioral research
• Familiarity with AI-specific threat vectors: prompt injection, jailbreaks, RAG poisoning, or misuse patterns in agentic systems
• Background in trust and safety, content policy, or a research-adjacent operational role at a technology company
• Experience building zero-to-one processes in research or safety contexts
• Prior exposure to agentic AI systems and the unique safety challenges introduced by tool use, multi-step reasoning, and autonomous execution