Technical Product Lead - Persistent Memory & Proactive Intelligence (Remote)

International Data Group

7d•$180,000 - $225,000•Remote

About The Position

Overview About the Role & Team IDC is building the next generation of AI-powered intelligence platforms that transform how technology decisions get made. Our platform re-imagines the way decision-makers discover and interact with trusted research and data, and is foundational to IDC's future. We are looking for a Technical Product Lead to own the product vision and strategy for the persistent memory and proactive Intelligence. This mission is twofold: make the platform remember users across sessions and over time, and make it proactively alert them when the intelligence they care about changes. Memory and living intelligence are deeply interdependent — memory tells the system what to monitor, and proactive delivery is what makes memory most valuable. You will define what the platform remembers, how it surfaces that knowledge, and when it reaches out proactively. This means setting memory scope policy (what gets remembered and what doesn't), defining the boundary between useful personalization and PII risk, establishing materiality thresholds for change detection, and designing the opt-in/opt-out model for proactive alerts. You will work alongside a dev lead and a cross-functional team of 4-8 engineers spanning AI/LLM and backend infrastructure disciplines. This is a product leadership role embedded in a delivery pod — you will own the backlog, author requirements, define quality criteria, and make scope and prioritization decisions daily. You are the person the engineering team turns to when they need to know what to build next and why.

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.

Nice To Haves

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

Responsibilities

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