Product Manager, GTM Automation

About the role

This role centers on building the foundational automation systems for Block, impacting how work flows and decisions are made across the company. The products you develop will power automation in critical areas like customer support, risk, compliance, sales, marketing, and internal operations. Success means creating efficient, scalable systems that enhance the company's speed and operational capabilities.

As a Product Manager, you will own the strategy and roadmap for AI products, identifying automation opportunities based on user needs and measurable business outcomes. This involves translating complex problems into clear product directions and requirements. You will work closely with machine learning engineers, data scientists, and researchers to define model goals, data strategies, and evaluation metrics.

A key part of the role involves designing and executing experiments to rapidly test ideas and learn from results. You will define product behavior across various scenarios, including success paths and edge cases, and establish metrics for accuracy, safety, and reliability. Collaboration with design, legal, security, and compliance teams is essential to build intuitive, transparent, and responsible AI solutions from concept to continuous improvement.

The annual salary for this position ranges from $110,000 to $165,000.

Skills that matter here

• product management experience: This role requires 7 to 10 years of experience, specifically with a track record of shipping AI or ML-driven products.
• machine learning systems: You will need deep technical intuition regarding training loops, evaluation, prompt design, data pipelines, and real-time inference constraints for ML systems.
• structured experiments: The role involves running experiments like A/B tests and offline model evaluations to test ideas and learn quickly.
• communication skills: Clear and compelling communication is necessary to engage with executive, technical, and operational audiences.
• regulated environments: Experience in scaled, high-stakes, or regulated settings such as risk, compliance, or operations is important for shipping responsible AI.
• LLMs, multimodal models, or applied generative AI: Hands-on experience with these specific AI technologies is expected for developing advanced automation products.

Who this role suits

• You have a strong ownership mindset and can drive complex initiatives across teams independently.
• You possess a deep technical understanding of machine learning systems and their practical applications.
• You are adept at translating ambiguous problems into clear product directions and requirements.
• You thrive in environments that require collaboration with diverse teams, including legal, security, and compliance.

From the employer

• Own the strategy and roadmap for AI-powered products that matter
• Identify automation opportunities rooted in real user pain and measurable business outcomes
• Turn ambiguous, high-stakes problems into clear product direction and requirements
• Partner deeply with ML engineers, data scientists, and researchers on model goals, data strategy, evaluation, and quality thresholds
• Design and run experiments to test ideas fast and learn even faster
• Define product behavior across success paths, failures, and edge cases
• Set and own metrics for accuracy, safety, latency, reliability, and user trust
• Work with design to build human-AI interactions that are intuitive, transparent, and safe
• Collaborate with legal, security, and compliance to ship responsible AI in regulated environments
• Lead cross-functional execution from concept to launch and continuous improvement

• 7 to 10 years of product management experience, with a strong track record shipping AI or ML-driven products
• Deep technical intuition around machine learning systems, including training loops, evaluation, prompt design, data pipelines, and real-time inference constraints
• Experience running structured experiments such as A/B tests and offline model evaluations
• A true ownership mindset and the ability to drive complex initiatives across teams without waiting for permission
• Clear, compelling communication skills for executive, technical, and operational audiences
• Experience working in scaled, high-stakes, or regulated environments such as risk, compliance, or operations
• Strong understanding of AI quality, safety, and responsible use
• Hands-on experience with LLMs, multimodal models, or applied generative AI