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Hellyeah AI

Senior Tech Product Manager

Reposted 7 Days Ago
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In-Office
San Francisco, CA, USA
Mid level
In-Office
San Francisco, CA, USA
Mid level
The role involves leading AI-driven advertising product strategy, collaborating with engineering teams, and using data to optimize ad performance.
The summary above was generated by AI
Technical Product Manager (Ads / AI Growth) — TPdM📌 Role Overview

We are looking for a Technical Product Manager (TPM) to lead the development of AI-powered advertising and growth products.

You will sit at the intersection of AI systems, advertising platforms, and performance growth, translating complex ad-tech and data problems into scalable product and system solutions that directly impact revenue and marketing performance.

This role requires a strong combination of product thinking, technical depth, and understanding of digital advertising systems.

🎯 Key Responsibilities1. AI Ads Product Strategy
  • Define the product strategy for AI-driven advertising systems, including:

    • AI-generated ad creatives (copy, image, video)

    • Automated campaign optimisation

    • Audience targeting and personalisation systems

  • Identify high-impact opportunities to improve core metrics such as ROAS, CAC, CTR, and conversion rate

  • Translate growth and marketing needs into structured product and system requirements

2. Ads System & Technical Design
  • Work closely with engineering teams on the design of core advertising systems, including:

    • Ad ranking and recommendation systems

    • Bidding and budget allocation mechanisms

    • Attribution and measurement models

  • Understand and define end-to-end data flows: User events → tracking → data pipelines → modeling → optimization loops

  • Evaluate trade-offs between performance, scalability, latency, and cost

3. AI-Driven Growth Products
  • Build and scale AI-powered advertising products, such as:

    • Automated creative generation systems (text/image/video)

    • Campaign optimization agents (budget, bidding, targeting)

    • Intelligent decision-making systems for ad performance improvement

  • Design feedback loops between model outputs and real-world advertising performance

4. Cross-functional Execution
  • Partner closely with engineering, data science, and growth teams to deliver high-impact products

  • Write PRDs, technical specifications, and define clear success metrics

  • Drive execution across multiple stakeholders in a fast-paced, iterative environment

5. Data & Experimentation
  • Design A/B testing frameworks to evaluate ad performance and product impact

  • Use data to guide product iteration and decision-making

  • Define and track key metrics such as ROAS, LTV, CAC, funnel conversion rates

🧩 RequirementsMust-have:
  • 3–7 years of experience in Product Management, Engineering, Data Science, or Ads/Growth-related roles

  • Strong understanding of digital advertising ecosystems (Meta Ads, Google Ads, TikTok Ads, etc.)

  • Solid technical background (Computer Science, Engineering, or equivalent hands-on experience)

  • Ability to reason about systems, data pipelines, and/or ML models

  • Experience working closely with engineering teams on complex system-level products

Preferred:
  • Experience in performance marketing, growth, or ad-tech companies

  • Familiarity with:

    • Auction and bidding systems

    • Recommendation or ranking systems

    • Attribution models (last-click, multi-touch, incrementality)

  • Exposure to AI/ML systems (especially LLMs or generative AI)

  • Experience building 0→1 products in early-stage or fast-paced startup environments

🚀 Nice to Have
  • Experience building advertising automation or growth optimization tools

  • Strong intuition for marketing funnels (impression → click → conversion → retention → LTV)

  • Experience with generative AI systems for creative production

  • Background in quantitative fields (Computer Science, Math, Statistics, Economics)

🧭 What This Role Is Not
  • Not a purely marketing or growth operations role without technical depth

  • Not a Technical Program Manager focused only on execution and timelines

  • Not a pure engineering role without product ownership and decision-making responsibility

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