Product Manager, Agent Harness & Modelling

Cohere is the leading security-first enterprise AI company focused on building cutting-edge foundation AI models and products. They are seeking a Product Manager for the Agent Harness to oversee the execution layer of their AI platform, ensuring agents are reliable and capable while managing interactions between engineering and modeling teams.

Responsibilities:

• Define and own the roadmap for North's agent harness, including the agent loop, context engineering layer, tool orchestration, sandbox execution, and sub-agent delegation
• Serve as the primary interface between North engineering and Cohere's Modeling team, ensuring new harness capabilities are validated before being built and that neither team paints itself into a corner
• Own North's agentic evaluation framework, ensuring evals are compatible with both the North harness and Modeling's training infrastructure, and that they serve as a reliable bridge between product and research
• Engage enterprise customers to surface real-world agentic failures and translate findings into concrete product and model requirements
• Stay current with the open-source and commercial agent ecosystem and drive adoption decisions that keep North's architecture aligned with emerging standards

Requirements:

• 5+ years of product management experience in agentic AI systems, developer infrastructure, or applied ML products
• Deep understanding of modern LLM agent architectures, including multi-agent systems, tool-augmented reasoning, memory and retrieval, programmatic orchestration, RAG, and long-horizon execution
• Strong grasp of agentic evaluation design, including how to measure task completion, failure recovery, and long-horizon reliability, and how to diagnose model vs. scaffolding gaps
• Technically deep enough to contribute to architecture decisions at the implementation level: comfortable reviewing and shaping design docs, reasoning about async execution patterns, sandboxed environments, filesystem design, and the tradeoffs that come with building harness capabilities into a production platform
• Ability to flex between ML research conversations and engineering architecture discussions with equal fluency
• Track record of shipping platform-layer products with demonstrated impact on reliability, performance, or capability
• An active practitioner of agent frameworks who regularly builds with and follows the latest developments in open-source harnesses, coding agents, and orchestration tools in both professional and personal work
• Hands-on experience with enterprise agentic deployments: multi-tenant orchestration, tool permissioning, audit trails, and compliance requirements
• Familiarity with infrastructure constraints relevant to enterprise deployments: on-premises environments, scalability challenges, and the operational tradeoffs of running complex agent workloads in restricted or air-gapped settings
• Prior work at the intersection of research and product, translating nascent model capabilities into shipped product features
• Background working within or closely alongside an ML research or post-training team