Description
People.ai is an AI-powered foundational data platform that helps customers unlock go-to-market success & growth by providing teams with solutions built specifically for their needs. Providing enhanced pipeline visibility, more actionable insights, and a single source of truth for all sales activities. People.ai’s unique dataset, consisting of trillions of sales activities, millions of deals, 160 million business contacts, and 69 approved patents related to AI-based business insights, sets the company apart. Companies such as Verizon, IBM Red Hat, Snowflake, Zoom, and Palo Alto Networks rely on their enterprise-ready, patented AI technology.
At People.ai, we believe that people enrich the world around them in countless ways. We believe that the more time they spend applying their creativity, resourcefulness, and critical thinking to activities that matter most in their professional life, the more effective a professional they become. Our team is a diverse, outspoken group of creatives and critical thinkers, hyper-focused on driving change and growth. We embrace different. We applaud non-traditional career paths. We're inspired by people who have made processes their own.
As the SalesAI Account Execution and Opportunity Execution Product Lead, you will spearhead the creation of next-generation tools that help sellers do their jobs more efficiently and empower sales leaders with precise, AI-driven insights. This is a high-impact opportunity to own the end-to-end product vision, collaborate with cross-functional teams, and deliver innovation that transforms how businesses project and achieve their revenue goals.
Responsibilities:
- Define Product Vision and Roadmap - Create and communicate a compelling long-term vision for the Account Execution and Opportunity Execution product.
- Lead Cross-Functional Development - Collaborate with engineers, data scientists, and designers to build AI-driven Account Execution and Opportunity Execution features.
- Drive User-Centric Design - Conduct user research to understand the specific needs and pain points of sales teams and revenue leaders.
- Coordinate Stakeholder Alignment - Manage trade-offs between user needs, technical constraints, and business objectives to deliver a balanced solution.
- Evangelize the Product - Define and track key performance indicators (KPIs), such as forecast accuracy, user adoption, and engagement.
Requirements:
- Years of Experience: Minimum of 4–6 years in product management, with at least 2 years in a senior or staff-level role.
- Education: Bachelor’s degree in a technical field (e.g., Computer Science, Computer Engineering, and similar). A Master’s degree is not required but a plus
- AI/ML Background: Proven experience working with AI/ML-driven products, particularly in sales or Account Execution and Opportunity Execution tools.
- Sales Domain Expertise: Deep understanding of sales processes, CRM systems, and sales methodologies.
- Enterprise Experience: Experience building and scaling enterprise-grade software products.
- Start-Up Experience: Experience building products in a high-growth or start-up environment.
Headquartered in San Francisco, CA, People.ai is backed by Y Combinator and Silicon Valley’s top investors, including ICONIQ Capital, Andreessen Horowitz, Lightspeed Venture Partners, Akkadian Ventures, and Mubadala Capital. People.ai is listed in the top 20 percent of Inc 5000 companies, is a regular leader in our key categories on G2, and is on the Forbes list of America’s Best Startup Employers. For more information, please visit www.people.ai.
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A reasonable estimate of on-target earnings (OTE) is $135,000 to $155,000. Additionally, regular employees may be eligible for commissions or bonus programs (target included in OTE), equity, and benefits. The range is subject to change. People.ai takes into wide range of factors when determining an individual’s pay. These factors can include, skill set, training and experience, licensure and certifications, and location and metropolitan area.
People.ai
Artificial Intelligence
Consumer Research
Enterprise Software
Intelligent Systems
Machine Learning
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