Senior Product Manager, Applied AI

Metropolis•Los Angeles, CA

2d•Onsite

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 teams to identify high-impact bottlenecks and reduce process friction. The successful candidate will combine analytical product leadership with an understanding of complex operational workflows and modern AI architecture, applying structured product practices while moving quickly when AI initiatives call for a scrappier or vendor-heavy approach. Working closely with AI Engineers, business leaders, and vendors, this person will turn operational challenges into scalable agentic workflows, internal applications, and automation systems. The role includes defining roadmaps and requirements, developing and deploying AI solutions, measuring business impact, iterating with internal users, supporting adoption, and monitoring reliability and value. Metropolis uses an office-first model requiring corporate team members to work onsite at least four days per week.

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.
Demonstrated success driving internal process transformations, operational optimizations, or building 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 fluency 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 and a bias toward shipping quickly, testing iteratively, and solving 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.
Direct 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 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 quantifiable success metrics, and track outcomes such as time savings, error reduction, and cost impact.
Lead agile product development cycles, gathering feedback from internal users and iterating on deployed AI tools to improve output quality.
Oversee change management so internal tools and systems are adopted across business units and deliver sustained impact.
Monitor production reliability, internal tool adoption, and the business value delivered by deployed systems.
Prototype solutions directly rather than limiting the role to writing specifications for others.