
Senior/Staff/Principal Product Manager (AI Orchestration & Agentic Workflows)
EvenUp
Job description
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We’re looking for a Product Manager who will build the brain of our AI system: the orchestration layer that powers everything from intelligent playbooks to self-executing workflows to continuous learning systems. (Final leveling will be determined through the interview process)
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This isn’t about managing features. It’s about architecting how AI agents work together to transform how law firms operate—and defining what “agentic workflow” means for legal AI
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AI Playbooks: Build systems that allow firms to teach our AI what to look for, automatically running that intelligence across every case and document to ensure nothing falls through the cracks
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Smart Workflows: Create workflows that analyze case data, make decisions about when to act, and automatically route cases toward faster resolution and higher settlements
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Context Systems: Build knowledge graphs and dynamic prompting systems that give our AI a deep understanding of case history, firm preferences, and legal nuances
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Evaluation & Quality Control: Own the eval framework, prompt iteration systems, and quality feedback loops to ensure our AI is reliable, powerful, and continuously improving
Benefits
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Flexible working hours to match your style
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Offsites - get to meet your coworkers on a fully-expenses trip ever 6-12 months
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A variety of virtual team events such as game nights & happy hours
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Choice of medical, dental, and vision insurance plans for you and your family
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Flexible paid time off and 10+ holidays per year
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A stipend to upgrade your home office for fully-remote roles
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401k for US-based employees- Deep curiosity about agentic systems, including multi-agent architectures, tool-use, and chain-of-thought decision-making
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A “Startup DNA” mindset: scrappy, adaptable, and comfortable with the ambiguity of a fast-paced environment
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Location: San Francisco preferred
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4-8+ years in product management, ideally with AI/ML products, workflow automation, or B2B SaaS
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Technical fluency to work directly with AI engineers on prompt engineering strategies, eval metrics, and system architecture
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Experience with LLMs, RAG systems, or 0→1 product development is highly preferred