Technical Product Lead

Role Overview

• Own the product vision, roadmap, and backlog for the persistent memory and proactive intelligence
• Define memory scope policy: what the platform remembers, what it doesn't, and the boundary between personalization and PII
• Define the product model for proactive intelligence: materiality thresholds, briefing content scope, delivery channel preferences, and opt-in/opt-out design
• Author detailed requirements and acceptance criteria for memory tiers (compactification, cross-conversational retrieval, extractive memory) and living intelligence features (change detection, briefing composition, delivery routing)
• Make daily prioritization and scope decisions with the engineering team
• Define quality criteria for memory accuracy, retrieval relevance, and briefing usefulness — and work with the Quality & Evaluation function to make them measurable
• Collaborate with the Channel & Integration Pod to ensure memory and proactive delivery work seamlessly across web, MCP, email, and Slack/Teams
• Work with legal and compliance stakeholders on data governance, retention policy, and user control requirements
• Represent the pod's roadmap and progress to leadership

Requirements

• 6+ years of product management experience, with significant time spent on AI/ML-powered products, data platforms, or personalization systems
• Experience defining product strategy for systems that manage user data, preferences, or behavioral context — and navigating the privacy and governance questions that come with them
• Track record of working as an embedded product lead within an engineering team, owning a backlog and making daily prioritization decisions
• Ability to translate ambiguous product goals into concrete requirements, acceptance criteria, and quality metrics
• Strong technical literacy — you can engage with engineers on system design, data models, and architecture tradeoffs without needing to write the code yourself
• Experience working across multiple teams or pods, defining interfaces and dependencies between workstreams
• Clear, structured communication with both engineering teams and executive stakeholders
• Turns complex technical concepts into clear, actionable language that drives alignment and informed decision-making with non-technical stakeholders
• Proven ability to make well-reasoned, defensible decisions that balance trade-offs across scope, feasibility, and impact.
• Passion for using AI tools to sharpen product thinking — from requirements and PRFAQs to Jira tickets — and forming a clear, independent point of view.
• Preferred Qualifications: Experience with AI personalization, recommendation systems, or memory/context systems
• Background in event-driven or proactive product experiences (alerts, notifications, monitoring dashboards)
• Familiarity with LLM-based systems and the unique product challenges they present (non-determinism, evaluation, prompt engineering)
• Experience navigating data privacy and governance frameworks (GDPR, data retention, user consent models)
• Background in enterprise B2B product management

Benefits

• 15 vacation days per year (increases with tenure; carryover allowed)
• 10 paid sick days per year
• 1 week paid new parenting leave
• Flexible work options (remote, part-time, flexible hours)
• Health, dental, vision, and paramedical coverage for you and your family
• $1,600 annual healthcare spending account
• Employee Assistance Program for counseling and support
• Best Doctors medical second opinions
• Life, AD&D, and long-term disability insurance
• Retirement savings plan with company match (up to 4% of salary)
• $75/month technology allowance for home office or phone expenses
• Company-paid cell phone plan