Revenue Systems Engineer
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**Role Purpose**
Design, build, and own the production systems that power FrankieOne's revenue operations. The Revenue Systems Engineer is a senior technical role responsible for end\-to\-end ownership of data pipelines, AI/ML platforms, automation infrastructure, and internal tooling that enable the RevOps function to operate at scale. This is not a support or maintenance role — it is an engineering ownership role with direct business impact.
You will work within the Leverage Team, partnering closely with the Revenue Systems Engineer and the RevOps Manager to identify high\-leverage problems and translate them into reliable, measurable production systems embedded in daily workflows across operations, management, sales, and client teams.
**Key Responsibilities**
**AI \& Machine Learning Systems (\~35%)**
* Design, build, and maintain end\-to\-end ML systems including training pipelines, model serving, and API deployment for revenue\-impacting use cases (scoring, classification, prediction). * Develop and operate AI\-powered content generation and analysis systems that produce production\-ready output at scale. * Build evaluation pipelines, feedback loops, and regression monitoring frameworks to ensure ongoing model performance. * Own the full lifecycle of deployed AI systems, including architecture, deployment, performance monitoring, and continuous improvement. * Identify high\-value automation opportunities across the revenue workflow and design AI\-first solutions to address them.
**Data Platform \& Backend Engineering (\~30%)**
* Design and operate high\-throughput data pipelines processing millions of records per day across both batch and real\-time modes. * Build and maintain backend APIs and processing services that integrate HubSpot, Xero, Redshift, and other revenue\-critical systems. * Architect scalable, low\-latency data infrastructure that supports operational, analytical, and reporting needs. * Develop commission calculation engines, financial reconciliation systems, and contract data extraction pipelines. * Own data quality monitoring, alerting, and incident response for production systems.
**Internal Platforms \& Tooling (\~20%)**
* Build internal tools and dashboards (React, Python) that are adopted and used daily across sales, operations, and management teams. * Develop email processing, workflow classification, and automation APIs that remove manual work from operational processes. * Create reporting and analytics services for enterprise clients and account managers. * Build training data systems and evaluation infrastructure that enable the team to develop and iterate on AI capabilities. * Maintain and improve the existing portfolio of production RevOps tools with a focus on reliability and performance.
**Engineering Standards \& Collaboration (\~15%)**
* Take end\-to\-end technical ownership of projects, from architecture and scoping through to production deployment and ongoing operation. * Document systems, APIs, and data models to reduce key\-person dependency and enable team scaling. * Establish and maintain engineering best practices including code review, testing, monitoring, and deployment standards. * Partner with the Senior RevOps Manager to identify the highest\-leverage technical investments and translate business needs into engineering specifications. * Upskill and mentor the RevOps Manager in Python, automation, and AI tooling.
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