Metropolis
Senior Product Manager, Applied AI
$170K–$200K
Seattle, Washington, United States +2 · Manager · Full-time · Posted Oct 27, 2026
- Location
- Seattle, Washington, United States
Los Angeles, California, United States
New York, New York, United States - Experience
- 6+ years in product management or technical product leadership; at least 2 years focused on shipping AI-powered applications, LLM implementations, or process automation systems.
About the job
Leads internal Applied AI strategy and delivery, turning operational challenges into AI-powered workflows, applications, and automation that improve business outcomes.
What you'll do
- Prioritize the internal AI roadmap and translate business needs into engineering specifications and measurable success metrics.
- Partner with business leaders and AI Engineers to design, deploy, and iterate on internal AI applications, RAG implementations, prompt pipelines, and agentic workflows.
- Drive adoption and monitor reliability, usage, and business impact of deployed tools.
What they ask for
- 6+ years of product management or technical product leadership experience, including at least 2 years focused on shipping AI-powered applications, LLM implementations, or process automation systems.
- Track record of internal process transformation, operational optimization, or building tools for internal business stakeholders.
- Practical understanding of LLMs, prompt systems, agentic patterns, and RAG architectures; hands-on fluency with AI tools, prompt engineering, AI coding agents, and rapid prototyping.
- Working familiarity with data architectures, data pipelines, and cloud infrastructure, including SQL, Snowflake, and AWS.
Nice to have
- Third-party vendor selection, evaluation, and integration for enterprise AI or software solutions.
- Experience scaling internal productivity tools or AI agents within high-growth technology companies.
Pay
$170,000.00 USD to $200,000.00 USD annually (base salary)
Tools
LLMs, SQL, Snowflake, AWS, RAG
AI focus
Lead internal AI transformation by developing AI-powered applications, prompt pipelines, RAG implementations, agentic workflows, and automation systems.
Model-written summary · the original posting is authoritative