Principal Product Lead, eDiscovery

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🕒 il y a 1 mois

🗣️🇺🇸🇬🇧 Anglais requis

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Casepoint

501 - 1000 employés

Fondée en 2008

☁️ SaaS

🏛️ Gouvernement

📋 Conformité

SaaS • Government • Compliance

Casepoint est une plateforme de découverte électronique et de découverte de données juridiques basée sur le cloud et alimentée par l'IA, qui aide les organisations à identifier, collecter, préserver et analyser des données liées aux aspects juridiques, réglementaires et de conformité à grande échelle. La plateforme offre un gel juridique, la gestion des demandes FOIA, des collectes et traitements sécurisés dans le cloud, des connecteurs intégrés et des API ouvertes, ainsi qu'un examen et des analyses pilotés par l'IA (CaseAssist) pour accélérer les enquêtes, les litiges et les flux de travail de conformité. Casepoint met l'accent sur la sécurité de niveau militaire et les certifications (y compris FedRAMP et les niveaux DoD IL) pour servir les agences gouvernementales, les entreprises et les cabinets d'avocats nécessitant des solutions de découverte de données et de conformité défendables et sécurisées.

Description

• Own the eDiscovery product roadmap across the full EDRM lifecycle, making crisp sequencing decisions and communicating tradeoffs clearly as new data emerges. • Stay close to customers (law firms, corporate legal, and government) to map real workflows and validate direction early, before major investment. • Move fast from idea to artifact: use AI-assisted development tools and rapid prototyping techniques (including vibe coding) to create working demos that accelerate learning, alignment, and decision-making. • Lead lean, cross-functional product squads (Engineering, Design, QA) to ship high-quality releases with momentum, with clear outcomes, measurable success criteria, and strong day-to-day execution. • Partner tightly with Sales and Customer Success to sharpen positioning, support critical pre-sales moments, unblock escalations, and turn market feedback into practical product actions. • Define success metrics, instrument learning, and run the post-launch loop, measure impact, diagnose gaps, and refine the product based on evidence. • Evaluate build, buy, and partner options across the legal tech ecosystem, making pragmatic recommendations and taking bold bets when they materially improve customer outcomes and durable differentiation.

🎯 Exigences

• Demonstrated experience in eDiscovery, legal technology, or a closely related domain, with a strong working knowledge of EDRM workflows and the needs of legal and compliance users. • A track record of delivering enterprise B2B SaaS products with engineering teams, translating ambiguity into clear requirements, defining acceptance criteria, and driving work through release. • A builder mindset: you take initiative, move with urgency, and find pragmatic paths forward without waiting for perfect conditions. • Comfort using AI tools, vibe coding environments, and low-code platforms to build working prototypes and demos that accelerate alignment and decisions. • High energy and a positive, solutions-oriented attitude, bringing momentum to cross-functional teams and raising the bar for execution. • Clear, concise communicator who can synthesize product concepts and learnings for customers, leadership, and cross-functional partners. • Impact-driven and analytical: you test bold ideas, measure results, and focus effort on what materially improves customer outcomes. • Sound judgment in prioritization, with a consistent ability to make and defend sequencing decisions based on evidence rather than pressure or opinion. • Highly coachable: you seek feedback early and adjust quickly. • Experience working across Sales, Customer Success, and Engineering to align teams on shared goals and translate market and customer signals into actionable product decisions. • A collaborative, accountable approach to cross-functional work, with a focus on outcomes rather than activity and a habit of following through on commitments. • Comfort operating in ambiguity, making reasonable decisions with incomplete information, learning fast, and adjusting course as technology, market dynamics, and customer expectations evolve.

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