Deal Desk Manager

Role overview

Runpod is building the core platform that lets developers create and operate custom AI systems at scale. The company serves more than 500,000 developers worldwide and has surpassed a $120M+ annual recurring revenue run rate. Since launching in 2022, it has expanded quickly by creating infrastructure designed specifically for modern AI workloads, with support for deployment across cloud, on-premises, and hybrid environments. As a remote-first organization with a globally distributed team, Runpod is focused on powering the next generation of AI infrastructure.

The Revenue Operations team owns the systems, processes, and commercial framework behind Runpod’s enterprise sales engine. Within that function, the Deal Desk team partners with Sales, Finance, Legal, and Customer Success to move complex enterprise agreements efficiently while preserving pricing discipline and operational accuracy.

The Deal Desk Manager will lead the quote-to-close workflow and the broader commercial governance process. This role is accountable for improving enterprise deal speed, maintaining pricing consistency, aligning with revenue recognition requirements, and ensuring contract controls are in place. The right candidate will have worked with sophisticated deal structures in fast-growing SaaS or infrastructure businesses.

You will help design and scale the operating structure that supports Runpod’s expanding enterprise motion. The work will influence deal throughput, pricing governance, forecast reliability, and overall operational scalability. You will also contribute to AI-enabled commercial operations that reduce manual work and improve efficiency.

Responsibilities

• Lead the review and approval flow for enterprise deals that fall outside standard terms.
• Support tailored pricing models, savings plans, multi-year agreements, and volume-based discounts.
• Define and enforce service-level expectations for Deal Desk support in partnership with Sales.
• Act as the main operational point of contact for Account Executives handling complex transactions.
• Own CPQ setup and administration together with Revenue Operations and Finance.
• Maintain pricing logic, discount tables, approval paths, and product catalogs inside the quoting system.
• Work with Sales leadership on quote formats and proposal processes.
• Apply commercial governance standards for pricing and discounting.
• Coordinate with Finance on booking rules and revenue recognition considerations.
• Coordinate with Legal on contract review steps and approval routing.
• Preserve pricing precedent and deal history documentation.
• Manage the repository of signed contracts and keep records aligned in the CRM.
• Build processes for renewals, amendments, and expansion-related workflows.
• Partner with Customer Success on renewal operations.
• Ensure contract terms and deal values are accurately entered in CRM systems.
• Identify risks tied to approvals, revenue recognition, or forecast accuracy.
• Support quarterly close activities and booking accuracy checks.
• Use AI tools to assist with contract review, workflow automation, pricing analysis, and approval routing.
• Assess AI solutions that can improve Deal Desk speed and scale.
• Stay informed on emerging best practices in AI-supported commercial operations.

Requirements

• Background in Deal Desk, Sales Operations, or commercial operations within SaaS, PaaS, IaaS, or infrastructure businesses.
• Solid understanding of enterprise pricing, usage-based models, and contract governance.
• Hands-on experience with CPQ tools such as Salesforce CPQ, DealHub, or Conga.
• Strong working knowledge of CRM systems; HubSpot experience is especially relevant.
• Understanding of revenue recognition concepts and enterprise contract structures.
• Proven ability to collaborate across Sales, Finance, and Legal.
• Excellent organization and communication skills.
• Comfort managing several complex deals at once.
• Regular use of AI tools for automation or commercial operations work.
• Must successfully complete a background check.
• Preferred: experience in cloud infrastructure, AI infrastructure, developer tools, or ML platforms.
• Preferred: exposure to usage-based pricing and savings plan structures.
• Preferred: experience implementing or migrating CPQ systems.
• Preferred: familiarity with CLM tools such as Ironclad, Juro, or DocuSign CLM.
• Preferred: experience supporting enterprise go-to-market teams in high-growth environments.

Perks and benefits

• Competitive base salary in the range of $125,000 to $180,000, with final compensation adjusted during interviews based on experience, qualifications, and location.
• Equity participation through stock options for all team members.
• Medical, dental, and vision coverage.
• Flexible paid time off.
• Remote-first culture with collaboration centered around Slack.
• Opportunity to work on advanced AI infrastructure with a team that values ownership, learning, and culture.
• $1,200 home office and equipment stipend to help set up your workspace.

Eligibility and additional information

Runpod is an equal opportunity employer and is committed to a workplace free from discrimination. The company welcomes qualified candidates regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, protected veteran status, disability status, or other legally protected characteristics.

The company welcomes qualified candidates who are eligible to work in the United States, but it is currently unable to sponsor employment visas.

This role is remote-first. The location provided for the listing is Akuhaito, Nagaland, India, but the role description emphasizes distributed remote work.

Company context

Runpod was founded in 2022 and operates at the intersection of developer productivity and production-grade AI infrastructure. Its platform supports flexible deployment across cloud, on-premises, and hybrid environments for teams moving from experimentation to production.

The role sits inside Revenue Operations and directly supports the enterprise sales motion, with an emphasis on scalability, accuracy, and AI-assisted process improvement.