Principal Product Manager, AI Workflows

ABOUT THE TEAM

Mural helps teams think, decide, and follow through together. AI made producing content cheap. The AI Workflows team builds the AI and agentic experiences inside Mural that help teams reach decisions and keep them.
You will own the outcomes for new AI experiences from first idea to proven value. You will partner with the Engineering Manager and the Agentic Design Director for AI Workflows as counterparts, and together you will own the strategy. You will work with a wider team of engineers, ML engineers, designers, and product managers, moving from hypothesis to working prototype to evidence in weeks, not quarters. You will build prototypes yourself and decide what ships, what changes, and what we stop, based on what users do and what the evals tell us.
Set strategy for AI Workflows together with your engineering and design counterparts, own the outcomes and the evidence behind what we build, and engage deeply in the end-to-end user experience
Find the team workflows where AI adds clear value, at the intersection of collaboration, alignment, and decision making.
Build working prototypes with modern AI tools (Claude, Cursor, Codex, or similar) to test ideas with users before committing further investment.
Define product-quality evals with engineering that measure usefulness, trust, and reliability, and own the call on whether an experience meets the bar to ship.
Decide with engineering and ML when to use frontier models, when to route across models, when to bring in a new model, and when a model of our own is worth building.
Understand the cost to serve each workflow, and work with growth and finance on how usage is metered and what the unit of value is.
Set up the data loops that improve quality, including what we collect, how we label it, and how it feeds evals and model work.
Work with design, engineering, marketing, sales, legal, and security teams to align on shipping decisions.
7+ years in product management, including shipping at least one AI product from concept to real users.
Recent hands-on experience building agentic or LLM-based products, including what went wrong and what you changed.
Technical fluency to design and read evals, and to work as a peer with engineers and ML engineers on context management, latency, reliability, and failure modes.
Understanding of AI unit economics, including cost to serve, usage-based metering, and how model choices change margin.
Experience creating structure where no playbook exists.
Experience with collaboration or productivity software.
Experience with forward-deployed or customer-embedded product work.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.