Staff Product Manager, Agentic Quoting Tools

Xometry•Waltham, MA

2d•Hybrid

About The Position

Xometry is hiring a Staff Product Manager to own the end-to-end request-to-quote experience for its most important customers. The role sits in the Pricing and Manufacturability (P&M) group alongside product managers for cost prediction, pricing, and Design for Manufacturability (DFM), and reports to the head of P&M product. It requires defining a roadmap from ambiguous signals and improving quote turnaround time, cost per quote, quote accuracy, and quote-to-order conversion on the human-assisted path. The Product Manager will redesign the request funnel across channels such as email, text, uploads, and agents; determine which work should be handled by agents, people, or self-service; and build agentic quoting capabilities, integrations, and staff tools. This includes agents that read requests and files, build quotes, and propose margin and lead time; MCP integrations connecting agents and people with Salesforce, quoting systems, file storage, and the ERP; and internal quote review, pricing, and summary tools. The role also makes human pricing decisions structured data to support future predictions and agent runs. The position calls for continuous discovery with quoters, account managers, customers, and other staff; prototype-first decisions; clear evaluation criteria and monitoring for AI features; and a 6-to-12-month roadmap aligned across Engineering, Data Science, Sales, Quoting Operations, and Finance. The Product Manager is expected to work spec-first, use agentic tools to investigate systems and prototype, and share effective AI workflows with peers. This role requires a hybrid schedule of three days per week at the Waltham, Massachusetts, or North Bethesda, Maryland, office. It is described as a startup pace within a public company, with an open problem and metric rather than a fully scoped backlog.

Requirements

8+ years of product management experience.
Direct ownership of a workflow or operations product between a sales or service organization and its customers, in a B2B, marketplace, or enterprise context.
Evidence of shipping AI or automation into an expert human workflow with guardrails, including judgment about when not to automate.
Experience integrating products across systems of record such as CRM, ERP, file storage, and messaging systems.
Working understanding of how agents connect to systems through tool protocols such as MCP.
Experience redesigning how requests enter a business across channels such as email, text, forms, APIs, or agents, with evidence of reduced drop-off.
AI-native practice, with examples of AI changing a team decision rather than only saving time.
Hands-on fluency with Cursor, Claude, or equivalent agentic tools.
A point of view on evaluating LLM features before and after launch.
Strong analytical fluency, including writing SQL, building dashboards, and identifying broken metrics.
Operational curiosity and ability to learn processes by working with the people who run them and earning their trust.
Exceptional written communication that enables operations leads, engineers, and executives to act on the same information.
Ability to make decisions under ambiguity and translate loosely defined problems into testable hypotheses and plans.
Bachelor’s degree in Business, Computer Science, Engineering, or a related field.

Nice To Haves

Experience in manufacturing, supply chain, pricing, or quoting; alternatively, evidence of learning an unfamiliar operational domain quickly.
Experience redesigning a request-to-fulfillment funnel across sales, service, and customer channels, with before-and-after metrics and adoption outcomes.
Experience building or owning an AI-agent integration with a system of record, including defining permissions, human approval requirements, and how errors are detected.
Experience shipping an AI or ML feature in a human-in-the-loop process and defining evaluation criteria, failure modes, and post-launch monitoring.
Evidence of a team making a different decision because of an AI-driven workflow, continuous customer signal, prototype-first decisions, or evaluation criteria defined before building.

Responsibilities

Own the end-to-end request-to-quote experience for the company’s most important customers.
Map quote-request journeys across intake channels, Sales, quoting, pricing review, and customer response; identify and remove unnecessary steps.
Improve quote turnaround time, cost per quote, quote accuracy, and quote-to-order conversion on the human-assisted path.
Redesign intake pathways to reduce drop-offs and determine when requests should be handled by an agent, routed to a person, or made self-service.
Own the roadmap for agentic quoting, including agents that read requests and files, build quotes, propose margin and lead time, and help promote human-priced parts into the instant-pricing engine.
Define what AI features should do, what counts as success or failure, what requires human confirmation, and what remains human work; maintain these standards through launch and afterward.
Own the integration layer connecting agents and people across Salesforce, quoting systems, file storage, and the ERP, including MCP servers, tool definitions, permissions, and audit trails.
Own internal quote review, pricing, and quote summary tools, and measure their adoption by quoting and sales teams.
Structure human pricing decisions, including overrides, margin changes, and lead-time adjustments, as data to improve predictions and agent runs.
Conduct continuous discovery with quoters and account managers, review inbound email and text queues and session recordings, and validate synthesized signals with customer and staff conversations.
Write queries, build dashboards, and specify the instrumentation and events needed to evaluate product outcomes.
Define and sequence a 6-to-12-month agentic quoting roadmap and secure alignment across Engineering, Data Science, Sales, Quoting Operations, and Finance.
Present progress against named outcomes to technical and non-technical audiences.
Work spec-first, investigate systems with agentic tools, develop prototypes in Cursor, Claude, and Figma Make, and write specifications suitable for engineers and coding agents.
Share effective and unsuccessful AI workflows and patterns with other product managers.

Benefits

Medical insurance
Dental insurance
Vision insurance
401(k) match
Generous paid time off, including vacation, sick leave, floating holidays, and fixed holidays
Maternity and bonding leave
Life insurance
Disability insurance
Employee assistance program (EAP)
Other wellbeing resources
Bonus and equity as part of total compensation