Senior Product Manager, Internal AI & Automation
New
J
JobgetherB2B SaaS
Based in the United StatesFull-TimeSenior
Salary140,000 - 210,000 USD per year
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Job Details
- Experience
- 5–10 years
- Required Skills
- Product ManagementSnowflake
Requirements
- 5–10 years of product management experience, with a demonstrated track record of building and launching products or internal tools.
- Strong systems-thinking skills and ability to understand how people, decisions, information, and processes interact within complex operational workflows.
- Hands-on experience building AI tools, automation workflows, agents, or internal products, including taking concepts from zero to a functional first version.
- Practical understanding of LLM capabilities, prompting, agent behavior, evaluation, reliability, and effective human-AI collaboration.
- Technical fluency with LLM APIs, agent frameworks, workflow automation platforms, and related modern AI tooling.
- Ability to independently prototype solutions using tools such as Claude or OpenAI APIs, n8n, Glean, or Snowflake.
- Strong product judgment and ability to make clear prioritization and tradeoff decisions in an ambiguous environment.
- Demonstrated ability to collaborate effectively with stakeholders across business and technical functions.
- Experience driving measurable business outcomes, adoption, efficiency gains, or operational improvements.
Responsibilities
- Lead rapid discovery across business functions to identify repeatable, high-value workflows where AI and automation can deliver significant efficiency or business impact.
- Own internal AI products end-to-end, from identifying the problem and defining the opportunity through prototyping, validation, launch, and ongoing optimization.
- Build and test initial solutions independently using LLM APIs, agent frameworks, no-code, low-code, and workflow automation tools.
- Partner with an AI Operations Engineer to transform successful prototypes into reliable, scalable, maintainable production solutions.
- Redesign processes from first principles, identifying how responsibilities and workflows can evolve when repetitive work is handled by AI.
- Define success metrics, adoption targets, rollout strategies, and usage playbooks for every solution launched.
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