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Intelligence and Automation Lead
Intelligence and Automation Lead
The Intelligence and Automation Lead will be a hands-on builder responsible for designing, building, and maintaining automated workflows and integrations to create a unified intelligence layer. This role involves developing executive dashboards, managing Confluence-based intelligence pages, driving AI adoption, and establishing AI governance practices across GSIP and Web3 PS divisions.
About the role
About the Role
This is a hands-on builder role from day one. You will write code, build pipelines, and ship automation every week. This is not a strategy-only position.
Responsibilities
- Own the Intelligence and Automation function for GSIP and Web3 PS — design, build, and maintain automated workflows (n8n or similar) for meeting notes processing, trip reports, intake routing, and reporting
- Develop and maintain integrations across Salesforce, Jira, Confluence, Atlas, and Neo4j to create a unified intelligence layer
- Design and build executive dashboards that surface real-time portfolio health, deal pipelines, partnership progress, and KPIs for leadership across both divisions
- Build and maintain Confluence-based intelligence pages — partner profiles, initiative trackers, competitive intelligence, and automated content pipelines
- Support the company's operating framework that separates strategic narrative, operational process, and intelligence/automation — building workflows around stage gates, milestone tracking, approvals, and templates
- Drive AI adoption across both divisions, identifying opportunities to increase operational efficiency through Claude, Neuronet, and other AI tools
- Own the Technical Strategy Roadmap for GSIP and Web3 PS, setting the long-term vision for automation and intelligence infrastructure
- Establish cadences for weekly reporting, monthly optimization reviews, and quarterly ROI reporting
- Measure and communicate the leverage gained through technology investments
- Continuously scout emerging AI capabilities, models, and tools on a weekly cadence. Run rapid experiments and present findings to the team
- Conduct regular demo sessions and hands-on training to ensure every team member across both divisions can effectively leverage AI tools. Lead by showing, not telling
- Attend key GSIP and Web3 PS meetings and working sessions to deeply understand operational context. Solutions must emerge from firsthand knowledge of how the team works
- Once automation is validated, hand off to operations leadership for integration into standard operating workflows. You pioneer; they scale
- Establish and maintain AI governance practices — ensuring AI decisions are traceable, compliant, and reversible
- Build predictive models for deal outcomes, partnership health, and initiative success. Surface anomalies and patterns before they become problems