Lead Product Manager, Agentic Ads Platform

Hightouch is an Agentic Marketing Platform powered by the industry-leading Composable CDP. With complete brand context, customer data, and performance history in one place, every marketer finally has the power to build and ship end-to-end campaigns themselves. Teams move faster, stay on brand, and get AI marketing that actually works.

Founded in 2019 and headquartered in San Francisco, Hightouch enables marketing teams to analyze performance, brainstorm ideas, and generate creative at a speed and quality that wasn't previously possible.

Named a Leader in the 2026 Gartner® Magic Quadrant™ for Customer Data Platforms, Hightouch is trusted by leading enterprises like Domino's, Spotify, Aritzia, Cars.com, Ramp, and PetSmart.

At Hightouch, our mission is to help our customers leverage data and AI to grow their businesses. The team is ambitious, impact-driven, efficient — and we believe humility, kindness, and compassion are essential to our success. If you're energized by velocity, obsessed with raising the bar, and want to build alongside people who care deeply about each other and our customers, we'd love to meet you.

Every large advertiser runs the same loop: strategist reviews performance data, decides what to test next, briefs a designer, waits for assets, hands them to a media buyer who builds campaigns across Meta and Google and TikTok, launches, monitors, repeats. The process is slow because creative production, campaign management, and performance analysis happen in three separate systems, and insights travel between them through decks, Slack threads, and weekly syncs.

Companies like Nike, Uber, and PepsiCo spend millions per month on digital ads and employ entire teams just to keep this loop turning. Most teams run 10 to 15 creative tests per month because every test requires manual work across multiple tools and teams. The result: most ad spend runs against stale creative, performance degrades from fatigue, and the gap between "what's working" and "what gets made next" is measured in weeks.

Advertising is uniquely high-leverage for AI agents because nearly every step in the workflow is now automatable, and the steps compound:

• Research. Agents can continuously monitor competitor ad libraries, auto-classify creative by format, hook, and message, and surface positioning gaps. What used to require a strategist spending hours in Meta Ad Library happens in the background, always current.
• Creative production. Generative models can now produce ad-quality images and video. The constraint has shifted from "can AI make this" to "can AI make this on-brand and on-spec for each platform." That is a solvable engineering problem, not a research problem.
• Campaign structure. Building properly structured campaigns (naming conventions, audience splits, placement targeting, budget allocation) across five ad platforms is tedious, rules-based work. Agents can do it faster and more consistently than humans.
• Optimization. Detecting creative fatigue, reallocating budget toward winners, and knowing when to rotate in fresh variants is pattern recognition across structured data. Agents excel at exactly this.
• The compounding effect. When one agent handles the full chain (research, production, activation, analysis, iteration) as a single workflow, the cycle time collapses from weeks to hours. A team that runs 15 tests per month can run 50+, not because any individual step got faster, but because the coordination cost between steps drops to nearly zero.

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