Product Manager, Agent Harness & Modelling
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Key skills for this role
About the Role
Cohere is seeking a Product Manager for Agent Harness & Modelling to own the execution layer of North's AI agents, including agent loop, context engineering, and model-scaffolding co-evolution.
Key Skills for This Role
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
- Own North's agentic evaluation framework, ensuring evals are compatible with both the North harness and Modeling's training infrastructure
- 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 tradeoffs
- 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
Full Job Posting
Role Overview
- We are seeking an Agent Harness Product Manager to own the execution layer that makes North agents reliable, capable, and production ready.
- This role sits at the intersection of three domains: Agent Loop and Execution, Context Engineering, and Model Scaffolding Co evolution.
- You will define how North agents plan and act across long, multi step workflows and ensure the execution environment is robust enough for the most demanding enterprise tasks.
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 produ
- 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.
Nice to Haves
- An active practitioner of agent frameworks who regularly builds with and follows the latest developments in open source harnesses, coding agents, and orchestration tools.
- 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 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.
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