Group Product Manager, Ads Product & Platform

Ready to be a Titan?

ServiceTitan is the operating system for the trades. As we deepen our investment in the advertising and local marketing ecosystem, we are hiring a Group Product Manager to own our Ads product and platform end-to-end — from campaign creation and budget management to tracking infrastructure, attribution, and measurement. This is one of the highest-leverage PM roles at the company: you will define how tens of thousands of home-service businesses discover, acquire, and retain customers through paid media.

This role sits at the intersection of performance marketing and AI. You will not just manage a roadmap — you will actively disrupt the traditional ads stack with AI-native features and position ServiceTitan as the authority on AI Engine Optimization (AEO) for the trades. You will also manage a senior PM with room to grow the team.

What you'll do:

Ads Platform & Infrastructure

• Own the full lifecycle of our ads platform: campaign management UI, budget pacing, creative management, and audience tooling.

• Define the roadmap for ad tracking and measurement — from pixel/tag infrastructure to server-side event pipelines and clean-room integrations.

• Drive multi-touch attribution strategy across paid search, LSA, display, and emerging AI-powered placements.

• Architect integrations with Google Ads, Meta, Microsoft Advertising, and category-specific ad networks relevant to home services.

AI & AEO Strategy

• Lead ServiceTitan’s AEO (AI Engine Optimization) strategy — helping our customers be discovered and recommended by AI-powered search engines, voice assistants, and LLM-driven referral surfaces.

• Identify and ship AI-native capabilities within the ads platform: predictive bid optimization, AI-generated ad copy, smart budget allocation, and automated campaign health scoring.

• Stay ahead of the rapidly evolving landscape — Google AI Mode, ChatGPT search, Perplexity, and what they mean for local service discovery and attribution.

Measurement & Insights

• Define and own the measurement framework: ROAS, CPL, LTV-adjusted ROI, and incrementality testing across channels.

• Build reporting surfaces that give our customers a single source of truth across organic and paid performance.

• Partner with Data Engineering to ensure our event collection, identity resolution, and attribution models are privacy-compliant and future-proof.

People & Cross-Functional Leadership

• Manage and mentor a PM team, including management of a senior PM. Set clear goals, run structured reviews, and grow their craft.

• Partner daily with Engineering, Design, Data Science, and Go-To-Market to ship with quality and speed.

• Represent Ads in executive reviews; translate complex technical trade-offs into crisp business narratives.

Who you'll bring:

Experience & Background

• 8–10+ years of product management experience, with meaningful tenure in ads, martech, or performance marketing platforms.

• Deep SaaS background; experience in vertical SaaS is strongly preferred — you understand the unique buying patterns, workflow complexity, and unit economics of industry-specific businesses.

• Proven track record shipping sophisticated ads or marketing technology: campaign management, programmatic, attribution, or analytics products at scale.

• Prior people management experience; you are a coach who makes PMs around you sharper.

Technical & Domain Mastery

• Expert-level fluency in the current digital advertising landscape: Google Ads (search, PMax, LSA), Meta, programmatic display, and the attribution ecosystem (GA4, third-party MMPs, server-side tagging).

• Hands-on familiarity with AI Engine Optimization concepts — how LLMs surface local businesses, what signals matter, and how to build products that help customers win in an AI-first discovery world.

• Comfortable reading data pipelines, reviewing API specs, and translating between business requirements and technical implementation.

• Strong quantitative instincts: you define success metrics before writing a PRD, and you know when a data set is telling you something real versus noise.