Product Manager, Agent Harness & Modelling

Cohere Cohere · AI Frontier · Toronto, ON · Product Management & Program Management

Product Manager for Cohere's North agentic AI platform, focusing on the execution layer (agent harness) which includes agent runtime, tool orchestration, context engineering, and co-evolution with the modeling team. The role requires deep understanding of LLM agent architectures and evaluation, with a focus on shipping platform-layer products.

What you'd actually do

  1. 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
  2. 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
  3. 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
  4. Engage enterprise customers to surface real-world agentic failures and translate findings into concrete product and model requirements
  5. Stay current with the open-source and commercial agent ecosystem and drive adoption decisions that keep North's architecture aligned with emerging standards.

Skills

Required

  • 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
  • Ability to contribute to architecture decisions at the implementation level
  • Ability to flex between ML research conversations and engineering architecture discussions

Nice to have

  • Active practitioner of agent frameworks
  • Hands-on experience with enterprise agentic deployments
  • Familiarity with infrastructure constraints relevant to enterprise deployments
  • Prior work at the intersection of research and product
  • Background working within or closely alongside an ML research or post-training team

What the JD emphasized

  • 5+ years of product management experience in agentic AI systems, developer infrastructure, or applied ML products
  • Technically deep enough to contribute to architecture decisions at the implementation level
  • Track record of shipping platform-layer products

Other signals

  • agentic AI platform
  • agent runtime
  • tool orchestration
  • context engineering
  • model-scaffolding co-evolution
  • agentic evaluation framework