Product Manager, Agent Harness & Modelling
Owns the product roadmap and execution layer for North’s enterprise AI agent harness, including orchestration, context management, evaluation, and model-scaffolding collaboration. Requires 5+ years of product management experience and deep technical fluency in LLM agents, applied ML, and production platform architecture.
About the job
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, validating harness capabilities before development.
- Own North's agentic evaluation framework and ensure evaluations work with both the North harness and Modeling's training infrastructure.
- Engage enterprise customers to identify real-world agentic failures and translate findings into product and model requirements.
- Monitor the open-source and commercial agent ecosystem and drive architecture adoption decisions.
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 task completion, failure recovery, long-horizon reliability, and diagnosing model versus scaffolding gaps.
- Technical depth to contribute to implementation-level architecture decisions, review and shape design documents, reason about asynchronous execution patterns, and understand sandboxed environments, filesystem design, and production tradeoffs.
- Ability to communicate fluently in ML research and engineering architecture discussions.
- Track record of shipping platform-layer products with measurable impact on reliability, performance, or capability.
Nice-to-Haves
- Active practice with agent frameworks, open-source harnesses, coding agents, and orchestration tools.
- Experience with enterprise agentic deployments, including multi-tenant orchestration, tool permissioning, audit trails, and compliance requirements.
- Familiarity with on-premises and air-gapped infrastructure, scalability constraints, and operational tradeoffs for complex agent workloads.
- Experience translating emerging model capabilities into shipped product features.
- Experience working within or alongside ML research or post-training teams.
Compensation & Benefits
- Competitive compensation and equity options.
- Weekly lunch stipend of $75/£75 or equivalent in local currency.
- Full health and dental benefits, including a separate mental health budget.
- RRSP matching, 401K, and pension scheme.
- Up to 6 months of 100% parental leave top-up for either parent.
- Annual enrichment benefits for arts and culture, fitness and wellness, quality time, and workspace improvements.
- Education and learning stipend for conferences, courses, and coaching.
- Six weeks of paid vacation.
- Travel budget for remote employees visiting other offices and an annual company offsite.
- Co-working benefit and a $500 home office stipend for remote employees.
Skills
Llm Agents, Multi-Agent Systems, RAG, Tool Orchestration, Agent Evaluation, Machine Learning, Async Execution, Sandboxed Environments, Filesystem Design, Python, Open-Source Agent Frameworks
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