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Salary: USD 175,000 - 200,000 / annual
Zip is an AI-powered enterprise procurement platform that helps companies orchestrate procurement across teams, tools, and suppliers. The company has raised $371 million at a $2.2 billion valuation and counts T-Mobile, OpenAI, AMD, Mars, and Dollar Tree among its customers.
As Manager, AI Operations, you will lead a team responsible for critical services and delivery, managing a mix of full-time employees and a large volume of contractors. You report directly to the Director of AI Forward Deployed Engineering and Operations and work closely with Customer Success, AI Forward Deployed Engineering, Product, and Engineering teams.
Key responsibilities include:
- Driving adoption of Zip's AI solutions across the customer base, partnering with Customer Success to move customers toward automated workflows and convert successful deployments into long-term revenue
- Owning the data and integration partnership evaluation program end-to-end, including coverage, reliability, and accuracy evaluation that determines which partners earn production integration status
- Ensuring platform quality and reliability by setting clear standards, testing processes, and release requirements
- Growing and leading the team, scaling capacity and establishing structure, performance standards, and operating cadence
- Owning throughput across the delivery pipeline from planning and prioritization through deployment, maintenance, and performance analytics
- Developing internal tools and automation to reduce repetitive tasks in quality assurance, support, and reporting
- Partnering daily across teams to keep delivery moving and resolve blockers
You are a hands-on team leader who maintains high standards while building the structure needed for a team to scale. You have a track record of managing operational teams to achieve measurable outcomes, with technical fluency to assess intelligent systems and data partners, combined with business sense to make critical project decisions.
REQUIREMENTS:
- Track record of owning an operational function with accountability for adoption, quality, and throughput, measured on outcomes rather than activity
- Experience growing and scaling a delivery team through systems, process, and coaching, with focus on lifting output quality as the team expands
- Technical fluency to judge AI quality, read an LLM evaluation framework, and assess a data partner's coverage and accuracy
- Strong commercial judgment to own partner evaluations and go/no-go decisions, balancing quality, cost, and strategic value
- Sharp prioritization under competing demands and communication discipline to surface risk to leadership
