Commonwealth Bank of Australia
Product Manager, GTM AI Systems
Zip is hiring a Product Manager, GTM AI Systems for a remote role open to applicants in United States. It pays $150k-$185k a year and Level rates it ; you can apply on Zip.
Level's read on this job
- Level rates this AI product manager role Works on AI ●●●○: the daily work is on AI products, without building the model.
- This is listed as a remote role.
- The posting mentions OpenAI, Claude and Claude Code among its tools and skills.
- Zip has 97 other open roles on Level.
- Posted in the last few days.
AI in this role
Zip is the AI platform for enterprise procurement — built for humans and agents working together. By orchestrating procurement across teams, tools, and suppliers with the help of AI agents, companies can secure the resources they need to innovate faster than ever before.
The world’s most influential enterprises trust Zip, including T-Mobile, OpenAI, AMD, Mars, Dollar Tree, and more. Together they’ve saved over $8 billion and processed over $500 billion in spend. Zip’s team includes product leaders from Apple, Airbnb, and Meta, as well as former procurement leaders from United Health, Sanofi, MGM Resorts, Discover, and NASA.
Backed by Adams Street, Alkeon, BOND, CRV, DST, Tiger Global, and Y Combinator, Zip has raised $371 million, most recently at a $2.2 billion valuation and has been recognized by Forbes Fintech 50, Fast Company's Most Innovative Companies, Inc. Best in Business, and LinkedIn Top Startups.
Your Role
You are the first product manager for GTM AI within Enterprise AI & Technology, owning the tools and agents that reach Field GTM & Operations, and the productivity and revenue gains they deliver.
You think AI-first and bring the ideas no one asked for: a seller gets a researched account brief, not a faster form. You prove the non-obvious idea with a cheap prototype, and you are equally clear about where AI does not belong.
You work directly with the business. You sit with Sales, Marketing, Customer Success, and Sales Ops to learn how the work really gets done, then write what gets built — the process flow, the data flow, the spec, the success criteria — and prototype it, so our GTM engineers build the right thing the first time.
You look at the whole picture, mapping the end-to-end flow across teams, systems, and handoffs before committing to a build, so we connect the revenue journey rather than ship point solutions that leave seams everywhere.
You define the approach where no playbook exists, balancing speed, quality, and adoption, and you set up the intake, prioritization, and release process for a function that did not have one.
You hold the quality bar personally, getting hands-on with the data, the prompts, the evals, and the agent workflows, because an AI capability the field cannot trust is worse than no capability at all.
You Will
Run discovery with sellers, marketers, customer success managers, and Sales Ops: shadow the work, find where time and deals are lost, set a productivity baseline, and turn requests into clear problems, priorities, and success criteria.
Own the roadmap and backlog for a portfolio of GTM AI capabilities, deciding with the GTM engineers what to build, what to configure, and what to say no to.
Own the GTM AI estate, not just the roadmap: evaluate and test vendors, make the build-versus-buy call and brief leadership on it, consolidate surfaces so the field has fewer places to go, and keep one source of truth for active and planned use cases.
Write the specs and prototypes the GTM engineers build from — example inputs, expected outputs, acceptance tests, integrations, and data flows — and turn them into reusable patterns, so each use case ships faster than the last.
Design AI experiences that turn signals into recommendations and automated action, not dashboards, with the reliability, security, and privacy requirements set up front.
Define and track adoption, usage, time saved, and ROI for each capability, and act on what they tell you, including retiring what does not work.
Decide what runs autonomously and what keeps a human in the loop — being able to automate something is not a reason to — then set the approval gates, evals, and quality checks that keep agent outputs trustworthy in front of customers and sellers.
Partner with Data and Engineering on the foundations behind GTM AI — entity resolution, enrichment, and scoring inputs from Salesforce, Gong, Clay, and Snowflake — and give every context source feeding the GTM AI outputs a named owner and a refresh cadence.
Work with Enablement to land new capabilities with the field, and gather structured feedback to shape the next release.
Qualifications
6+ years in product management, Sales Operations, GTM strategy, business systems, or solutions and forward-deployed engineering at a B2B SaaS company, owning cross-functional products end to end with accountability for outcomes, not output.
Strong GTM domain credibility: you know how Sales, Marketing, Customer Success, and Sales Ops work day to day, you are comfortable with sellers and their leaders, and you have improved sales productivity through product, automation and AI.
A builder's mindset: comfortable starting from an imperfect prototype, a track record of turning ambiguous needs into specs and workflows that get built and used, and judgment about where LLMs and agents fail and how to evaluate them.
Fluency with the GTM stack — Salesforce, Gong, Clay, Snowflake, and LLM tools such as Claude — plus CRM data models, APIs, and workflow orchestration.
Hands-on AI build skill: you have personally built working prototypes, agents, or automated workflows with tools such as Claude Code, not just used AI-enabled products, and you can show what you built, what broke, and what you changed.
Strong written communication, with the ability to simplify complex topics for senior stakeholders.
Nice to Haves
Experience building evaluation or governance practices for AI-generated content.
Hands-on experience with GTM AI tools such as Actively and Octave.
Experience as a GTM engineer, solutions architect, or forward-deployed engineer with strong product instincts.
The salary range for this role is $150,000 - $185,000. The salary for this position is determined based on a variety of job-related factors that may include location, relevant experience, education, or particular skills and expertise.
Perks & Benefits
At Zip, we’re committed to providing our employees with everything they need to do their best work.
📈 Start-up equity
🦷 100% health, vision & dental coverage options
🍽️ Catered breakfast, lunch, & dinner
🌴 Flexible PTO
🏋️♀️ ClassPass membership
🚍 Monthly commuter benefit
🚠 Team building events & happy hours
💻 Home office stipend
🛜 Phone/internet reimbursement
🍼 Paid parental leave
🧑🧑🧒🧒 Fertility stipend
💸 401k plan
🤖 AI token usage
We're looking to hire Zipsters and that means hiring people who take ownership, communicate openly, have an underdog mindset, and are excited to increase the pace of innovation for every business in the world. We encourage all candidates to apply even if your experience doesn't exactly match up to our job description. We are committed to building a diverse and inclusive workspace where everyone (regardless of age, religion, ethnicity, gender, sexual orientation, and more) feels like they belong. We look forward to hearing from you!
How we rate this
Product Manager, GTM AI Systems at Zip rates 73 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI product manager jobs at this level
Pay
- This job starts at
- $150k
- Typical AI product manager job
- $179k
This posting starts 16% below the typical AI product manager job. See AI product manager jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you check AI-generated content before it ships?
- What are the limits of OpenAI that you've run into, and how did you work around them?
- What's a project where you used Claude hands-on?
- Walk me through how you've used Claude Code in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: AI agents, AI Content, OpenAI, Claude, and Claude Code. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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