Senior Manager, Revenue Automation & AI

About the role

You will own the end-to-end automation and AI strategy for the revenue motion at OpenLoop, translating ambiguous operational problems into production-grade solutions. This role requires you to ship and maintain AI agents that are actively running in production, not停留在 a pilot or slide deck. You will design the intake and prioritization framework that determines which automation and AI initiatives move forward based on impact, effort, and capacity. The position demands deep, hands-on engagement with the tools you build, ensuring you personally validate workflows and agent behaviors on a regular basis. You will partner cross-functionally with Revenue Systems, Revenue Intelligence, Finance, and GTM leadership to align technical execution with business objectives. As a player-coach, you are expected to contribute directly to building critical automations while simultaneously leading and developing a team of analysts. Your work will focus on ensuring that automation is reliable, monitored, and defensible, so that the revenue engines operate consistently without manual intervention.

Key facts

What you'll do

Define and own the GTM automation intake and prioritization roadmap, scoring opportunities by impact and effort while reconciling them with team capacity and stakeholder demands.

Design, build, and maintain production AI agents that power revenue workflows, including prospecting, AI SDR operations, enrichment pipelines, MQL classification, intent filtering, and competitive intelligence generation.

Own the end-to-end automation layer across HubSpot, Jira, Slack, and Salesforce, ensuring that workflows triggered by deal stage, client status, and operational events execute reliably every time.

Establish and enforce quality standards for AI output, focusing on the business problem being solved rather than mere execution, with robust monitoring, alerting, and documented runbooks.

Develop and defend impact measurement models that track hours returned, cost avoided, and revenue influence, ensuring methodologies withstand Finance and board-level scrutiny.

Lead, hire, ramp, coach, and develop a dedicated pod of automation analysts, growing the team headcount in alignment with the expanding automation roadmap.

Partner with Revenue Enablement to drive adoption of new automations, ensuring that solutions are built for usage and embedded into the revenue operating cadence.

Collaborate with Revenue Systems during the active HubSpot to Salesforce migration to preserve automation integrity and AI functionality across the platform transition.

Evaluate and integrate emerging AI toolchains, including prompt design, tool use, evaluation frameworks, and failure handling, to maintain a competitive edge in automation capabilities.

Maintain a living inventory of automations and AI agents, documenting behaviors, dependencies, and ownership to support scalability and operational resilience.

Champion data hygiene and process discipline across CRM, financial systems, support platforms, and product data to ensure automation logic executes on clean and reliable inputs.

Translate ambiguous business problems into clearly defined automation requirements, success metrics, and phased implementation plans that stakeholders can understand and support.

Act as the primary technical and operational owner for the revenue automation function, making final decisions on scope, trade-offs, and acceptance criteria.

Build business cases and defend ROI numbers to Finance and executive stakeholders using rigorous analysis and transparent assumptions.

Requirements

Bring 5 or more years of hands-on experience in revenue operations, marketing operations, systems, or automation, with a track record of owning builds end-to-end.

Demonstrate prior experience leading a delivery pod in a formal management, tech lead, or player-coach capacity with direct reports.

Show expert-level proficiency in HubSpot, including workflows, custom objects, properties, and API integrations.

Have deep, practical experience with at least one automation platform such as Make.com, Zapier, Workato, or similar tools.

Have built AI agents in production, not just used ChatGPT, with demonstrated skills in prompt design, tool integration, output evaluation, and handling failure modes.

Possess strong judgment around AI output, knowing when to trust the model, when to investigate further, and when a seemingly correct answer is actually wrong.

Comfortably operate in messy, multi-system data environments that span CRM, financial systems, support tools, and product data.

Proven ability to construct a business case, quantify impact, and defend numerical conclusions to Finance and C-level stakeholders.

Have direct experience through a CRM migration or platform consolidation, with a strong preference for familiarity with HubSpot to Salesforce migrations.

Exposure to Clay, Claude Code, Salesforce, Zoho Desk, NetSuite, or Stripe data structures is a clear advantage in understanding integration patterns.

Background in healthcare or other regulated-data environments, including handling of PHI, is a preferred differentiator.

Nice to have

None specified.

Practical notes

None specified.