Product Manager, Agent Harness & Modelling

Stelle nicht auf LinkedIn

🕒 vor 5 Monaten

🇨🇦 Kanada – Remote

⏰ Vollzeit

🟡 Mittelstufe

🟠 Senior

✅ Produktmanager

👻 Geisterscore 51%

infoinfo

🗣️🇺🇸🇬🇧 Englisch erforderlich

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Logo of Cohere

Cohere

11 - 50 Mitarbeiter

🤖 Künstliche Intelligenz

🏢 Unternehmen

☁️ SaaS

Artificial Intelligence • Enterprise • SaaS

Cohere ist eine führende KI-Plattform, die Unternehmen fortschrittliche Sprachmodelle und einen integrierten Arbeitsbereich bietet, der auf Effizienz und Sicherheit ausgelegt ist. Mit einer Reihe von leistungsstarken generativen und Retrieval-Modellen ermöglicht Cohere Organisationen die Optimierung von Arbeitsabläufen, die Verbesserung der Datensicherheit und das Erschließen von Erkenntnissen über verschiedene Branchen hinweg durch mehrsprachige Fähigkeiten. Ihr Fokus auf maßgeschneiderte KI-Lösungen gewährleistet den Schutz kritischer Daten und erleichtert die nahtlose Integration in bestehende organisatorische Prozesse.

Beschreibung

• 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.

🎯 Anforderungen

• 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.

🏖️ Vorteile

• An open and inclusive culture and work environment • Work closely with a team on the cutting edge of AI research • Weekly lunch stipend, in-office lunches & snacks • Full health and dental benefits, including a separate budget to take care of your mental health • 100% Parental Leave top-up for up to 6 months • Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement • Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend • 6 weeks of vacation (30 working days!)

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