Senior Revenue Operations, AI Strategy & Solutions Architect
Seattle, Washington, United States of America
Full Time
3 hours ago
$110,000 - $142,500 USD
H1B Sponsor
Key skills
AICommunicationProblem SolvingSales
About this role
Role Overview
Act as the primary administrator and subject matter expert for our GTM tech stack such as Glean, ZoomInfo, LinkedIn Sales Navigator, and Lightcast, ensuring these tools drive quantifiable ROI.
Identify bottlenecks in the sales process and build automated solutions into existing or new workflows to increase GTM velocity.
Lead the charge in implementing and driving the adoption of AI tools within our revenue teams to optimize performance and efficiency.
Manage and optimize lead enrichment processes and drive pipeline solutions to ensure our sales teams are working with high-quality, actionable data.
Lead projects and build consensus with stakeholders to make data-driven decisions on growth strategy, ROI analysis, and operational optimizations.
Develop new metrics and dashboards to identify trends, capitalize on operational improvement opportunities, and prove the impact of our tech investments.
Requirements
3+ years of experience in revenue operations, business process roles, or strategic analytical roles at a high-growth company.
Tech Stack Expertise: Proven experience managing or implementing GTM tools (e.g., ZoomInfo, LinkedIn Sales Navigator, or similar lead enrichment platforms).
Automation Mindset: A proactive thinker looking to build processes and technical workflows that scale.
Analytical Power: A passion for turning complex data sets into meaningful business insights with a focus on business impact.
Technical Skills: Basic data architecture and process optimization experience required.
Communication: Strong written and verbal communication skills with the ability to interface with various stakeholders and leaders throughout the organization.
Problem Solving: Detail-oriented with the ability to problem-solve in both individual and group settings.
Academic Background: Degree in Finance, Economics, Computer Science, or a similar quantitative discipline.