Applied AI Product Manager

Sequoia Capital Global Equities is a remote-first team focused on uplifting communities through their app-based marketplace connecting healthcare professionals with workplaces. The Applied AI Product Manager will own product surfaces where AI can enhance customer experience, scoping problems, prototyping solutions, and measuring success metrics tied to customer value.

Responsibilities:

• Talk directly with customers and study tickets, workflows, and DD sessions to identify operational pain points
• Identify high-leverage opportunities where AI improves customer outcomes, not where it’s trendy
• Ship working prototypes, not slide decks. We move in days, not quarters
• Define success metrics tied to customer value, then hold yourself to them
• Work directly with LLMs, APIs, and product code. You don’t need to be an engineer, but you can’t be afraid of a codebase
• Build and validate prototypes quickly using AI tools, product code, APIs, and internal workflows
• Make hard scope calls. Say no to 80% of ideas so the 20% actually ships
• Ensure fixes remain durable by validating outcomes and continuously improving workflows

Requirements:

• You've shipped AI-powered features to real users (not just internal tools or demos)
• You think in tradeoffs, not best practices
• You're fast. Uncomfortably fast. You'd rather ship something imperfect Tuesday than something polished next month
• You can read code, query a database, and prompt an LLM with precision, not as party tricks, but as daily tools
• You have a strong bias for action and don't let problems linger too long
• You prefer seeing for yourself by going deep into customer sessions, tickets, and workflows instead of relying purely on consensus
• You validate and ship value quickly
• Talk directly with customers and study tickets, workflows, and DD sessions to identify operational pain points
• Identify high-leverage opportunities where AI improves customer outcomes, not where it's trendy
• Ship working prototypes, not slide decks. We move in days, not quarters
• Define success metrics tied to customer value, then hold yourself to them
• Work directly with LLMs, APIs, and product code. You don't need to be an engineer, but you can't be afraid of a codebase
• Build and validate prototypes quickly using AI tools, product code, APIs, and internal workflows
• Make hard scope calls. Say no to 80% of ideas so the 20% actually ships
• Ensure fixes remain durable by validating outcomes and continuously improving workflows