Intelligence & Automation Engineer
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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
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