Product Manager, GTM AI Systems

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.

• 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.

• 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.

• 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.

• 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.