Senior Product Manager, Applied AI

Metropolis•New York, NY

11h•$190,000 - $210,000•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 leaders in Finance, Operations, Go-To-Market, and other areas to identify high-impact bottlenecks and reduce process friction. The successful candidate will apply product rigor—including clear PRDs, disciplined roadmapping, and structured discovery—while adapting to fast-moving, sometimes vendor-heavy approaches where appropriate. Working alongside AI Engineers and vendors, the Senior Product Manager will turn operational challenges into scalable agentic workflows, internal applications, and automation systems that deliver measurable business impact. The role includes defining requirements and success measures, prototyping solutions, guiding development and adoption, and monitoring the reliability and value of deployed systems. Metropolis uses an office-first model requiring corporate team members to be onsite at least four days per week. The anticipated base salary is $190,000 to $210,000 annually. The total compensation package may also include healthcare benefits, a 401(k), 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.
Proven experience driving internal process transformations or 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.
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 GTM 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, tracking outcomes such as time savings, error reduction, and cost impact.
Lead agile product development cycles, gather feedback from internal users, and iterate on deployed AI tools to improve 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 only writing specifications for others to build.