Senior AI PM at Mural | Agentic Product Strategy Role

Mural; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Remote work flexibility

Remote-friendly culture

Job summary

Mural, a leading collaboration platform, seeks a Senior AI Product Manager to own AI workflows from idea to proved value. You will partner with Engineering Manager and Agentic Design Director for AI Workflows, collaborating across engineers, ML engineers, designers, and PMs to move from hypothesis to working prototype in weeks.

You will decide what ships, what changes, and when to stop, based on user data and eval results, building prototypes yourself and shaping strategy with cross-functional

Qualifications

• 7+ years in product management, including shipping at least one AI product to real users.
• Hands-on experience building agentic or LLM-based products and learning from mistakes.
• Technical fluency to design/read evals and work with engineers on latency, reliability, and failures.
• Sound judgment on model decisions: comparing models, routing, and when to fine-tune.
• Understanding AI unit economics, cost to serve, and usage-based metering.
• Experience owning outcomes while partnering with expert engineering and design leads.

Responsibilities

• Set strategy for AI Workflows with engineering/design counterparts and own outcomes.
• Identify workflows where AI adds clear value at collaboration/decision-making intersections.
• Build prototypes with modern AI tools to test ideas with users before large investments.
• Turn each release into a hypothesis with pass/fail criteria and decide on iteration or kill.
• Define product-quality evals with engineering to measure usefulness, trust, and reliability.

Skills

PM experience

AI product

LLM evals

Agentic models

Unit economics

Cross-functional

Decision making

Tools

Claude

Codex

MCP

Cursor

Job description

Senior AI PM at Mural | Agentic Product Strategy Role — Remote

Career Trajectory: This is a senior-to-staff level AI PM role with significant ownership — you're setting strategy, owning evals, and making ship/kill decisions. It's a strong career accelerator for PMs who want to specialize in AI product development at a time when this skillset commands a premium in the market.

Compensation Benchmarks: No salary is listed, but senior AI PMs at SaaS companies of Mural's scale (Series C/D stage, ~$50M+ ARR) typically earn $180,000–$240,000 USD total compensation in the US market. If Mural lags on cash, equity and mission may compensate — but candidates should negotiate firmly given the specificity of the LLM/agentic skills required.

Skills You'll Build:

• Hands-on agentic AI product development (Claude, Codex, MCP) — high demand skill
• LLM eval design and AI unit economics — rare and increasingly critical
• Prototype-to-ship velocity in AI-native workflows
• Cross-functional leadership without direct authority

Green Flags: "Weeks, not quarters" iteration pace signals a healthy bias for action. Partnering as a true peer with engineering and design (not above them) is a strong culture signal for collaborative, non-hierarchical teams.

Red Flags to Watch: No explicit salary, no benefits listed, and the scope is very broad — strategy, evals, prototyping, cost modeling, and user research all in one role. Confirm headcount and PM team size before accepting to avoid being spread too thin.

About the Team

Mural helps teams think, decide, and follow through together. AI made producing content cheap. It did not make agreement, commitment, or follow-through any easier. The AI Workflows team builds the AI and agentic experiences inside Mural that help teams reach decisions and keep them.

Your Mission

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.

What You'll Do

• 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.
• Turn each release into a hypothesis with pass/fail criteria, and make the call on whether to iterate, scale, or kill it.
• 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.
• Design agentic experiences that work in real multiplayer sessions, where people need to understand, steer, and correct what the agent does.
• Talk with users every week and bring what you learn back into the work.
• Work with design, engineering, marketing, sales, legal, and security teams to align on shipping decisions.
• Share what you learn across the product organization so other teams can adopt the practices that work.

What You'll Bring

Required:

• 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.
• Sound judgment on model decisions: comparing models, routing across them, adopting new ones, and deciding when fine-tuning or a custom model is worth it.
• Understanding of AI unit economics, including cost to serve, usage-based metering, and how model choices change margin.
• A record of launching, rebuilding, changing direction, and killing ideas based on evidence.
• Comfort making high-stakes decisions with incomplete information, and being candid about the tradeoffs.
• Experience owning outcomes while partnering with expert engineering and design leaders as true counterparts.
• Experience creating structure where no playbook exists.

Nice to Have:

• Experience with collaboration or productivity software.
• Experience with forward-deployed or customer-embedded product work.
• Experience with agent interoperability, including MCP.

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. Please contact us to request accommodation.

Is this role fully remote or does it require office presence? The role is listed for the USA without a specific city, strongly suggesting it is fully remote within the United States. No office location is mentioned in the posting. What level of AI/ML technical knowledge is required for this PM role? You need technical fluency to design and interpret evals, understand context management, latency, and failure modes, and make informed decisions about model routing, fine-tuning, and custom model development — peer-level collaboration with ML engineers is expected. Does Mural mention a salary range for this position? No salary range is disclosed in the job posting. Candidates should research market rates for senior AI PM roles and negotiate based on their LLM/agentic product experience. What AI tools and frameworks will I work with in this role? The posting specifically mentions Claude, Cursor, and Codex as examples of modern AI tools used for prototyping, along with agentic workflows and MCP (Model Context Protocol) for agent interoperability. How much autonomy does this role have in shipping decisions? Significant — you own the call on whether an experience meets the bar to ship, whether to iterate or kill a release, and which models to use. You set strategy jointly with engineering and design counterparts but own outcomes.

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