Senior Product Manager, Applied AI

Metropolis•Seattle, WA

12h•$170,000 - $200,000•Hybrid

About The Position

Metropolis is seeking a Senior Product Manager, Applied AI to lead internal product strategy and drive an AI-first operational transformation across the company. The role focuses entirely on internal AI initiatives, partnering with business leaders across Finance, Operations, Go-To-Market, and other functions to identify high-impact bottlenecks and reduce process friction. The successful candidate will combine strong product management practices—including structured discovery, clear PRDs, and disciplined roadmapping—with a flexible, fast-moving approach to AI initiatives. Working with AI Engineers and vendors, this person will turn operational challenges into scalable agentic workflows, internal applications, and automation systems that deliver measurable business impact. The position is part of Metropolis’s corporate team, which follows an office-first model requiring employees to be onsite at least four days per week. The anticipated annual base salary is $170,000 to $200,000 USD. Total compensation may also include healthcare benefits, a 401(k) plan, short- and long-term disability coverage, basic life insurance, stock options, and bonus plans.

Requirements

At least 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.
A proven track record of driving internal process transformations, operational optimizations, or software tools for internal business stakeholders.
Practical understanding of LLMs, prompt systems, agentic patterns such as tool calling and multi-step reasoning, and RAG architectures.
Hands-on experience building with AI tools, including prompt engineering, AI coding agents, and rapid prototyping.
Working familiarity with modern data architectures, data pipelines, and cloud infrastructure, including SQL, Snowflake, and AWS.
Exceptional communication and stakeholder management skills, including the ability to explain complex technical concepts to non-technical business leaders.
Strong change management instincts and user empathy to help non-technical teams transition to AI-first workflows.
Entrepreneurial drive, a bias toward shipping quickly and testing iteratively, and the ability to solve open-ended problems in a fast-paced environment.

Nice To Haves

Experience managing 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.
A Computer Science, Data Science, or related technical background.
Familiarity with enterprise security, compliance, and governance frameworks for enterprise AI usage.
Experience in hyper-growth startups or environments managing rapid organizational change.

Responsibilities

Prioritize the internal Applied AI product roadmap and translate ambiguous business challenges into prioritized engineering specifications and AI-first solutions.
Partner with business leaders across Finance, Operations, and Go-To-Market to map workflows, identify automation opportunities, and drive adoption of internal technology.
Collaborate with AI Engineers to design, scope, and deploy internal applications, prompt pipelines, RAG implementations, and agentic workflows.
Define requirements, PRDs, and measurable success metrics; track outcomes such as time savings, error reduction, and cost impact.
Lead agile product development cycles, gather feedback from internal users, and continuously improve deployed AI tools and output quality.
Oversee change management to support sustained adoption of new internal tools and systems across business units.
Monitor production reliability, internal tool adoption, and the business value delivered by deployed systems.
Prototype solutions directly rather than relying solely on specifications for others to build.