Responsibilities
- Develop and execute a strategic roadmap for AI and machine learning models aimed at increasing revenue and lowering costs through sales forecasting, churn prediction, target identification, and dynamic pricing.
- Continuously track model effectiveness, detect performance degradation, and coordinate timely updates or retraining to ensure alignment with evolving market dynamics.
- Design the architecture of a centralized 'Seller Action Hub' to streamline the sales technology environment and reduce system fragmentation and cognitive burden for over 500 sales professionals.
- Apply Action-Centric Insight and Design (ACID) methodologies to deconstruct sales workflows in prospecting, deal structuring, and pipeline management to uncover AI integration opportunities.
- Establish technical specifications enabling seamless integration between Google Gemini, Salesforce.com, and AWS-hosted legacy platforms for unified data access by AI agents.
- Evaluate and validate autonomous AI agents capable of performing data-based decisions and executing multi-step tasks such as outreach automation, risk assessment, and pricing adjustments.
- Lead the definition of strategic AI initiatives for go-to-market functions, aligning quarterly and annual projects with clear financial KPIs including EBITDA, gross margin, and net revenue retention.
- Collaborate closely with IT development teams to ensure technical delivery of AI solutions supports the strategic objectives of the sales organization.
- Develop and manage interactive reporting dashboards to track model outputs and key performance metrics in real time.
- Ensure all AI implementations comply with corporate policies including the Google AI Acceptable Use Guide, client-specific AI restrictions, and broader IT governance standards.
Responsibilities
- Define strategy to develop and implement AI machine learning models specifically focused on revenue optimization and cost reduction (e.g. forecast sales, predict churn, determine high probability targets, dynamic pricing strategies)
- Monitor model performance: Identify drift and orchestrate the retraining/update of models as necessary to maintain predictive accuracy and relevance to market conditions
- Architecture of the "Seller Action Hub": Reimagine the frontline sales tech stack philosophy to create a unified AI workspace that reduces "systems overload" and "cognitive drag" for 500+ sellers.
- Workflow Deconstruction: Utilize Action-Centric Insight and Design (ACID) to analyze sales activities in prospecting, complex deal structuring, and pipeline governance to identify opportunities for AI augmentation or automation.
- Cross-System Interoperability: Define the technical requirements to enable Google Gemini, Salesforce.com, and AWS-hosted legacy systems to work together, allowing AI agents to fetch real-time intelligence across disparate datasets.
- GTM Agentic Strategy: Identify and vet the use of autonomous AI agents capable of making data-driven decisions and executing complex actions, such as automated outreach, deal risk analysis, and pricing optimization.
- Strategic Requirement Definition: Lead the process of defining annual and quarterly AI GTM projects, ensuring that all proposed AI pilots are tied to measurable improvements in EBITDA, Gross Margin, and Net Revenue Retention (NRR).
- IT Partnership: Work hand-in-hand with IT development teams to bring AI projects to life, ensuring that technical execution aligns with the strategic needs of the sales organization.
- Reporting and Communication: Create and maintain interactive dashboards and reports to visualize key performance indicators and model outputs
- Compliance: All AI related projects, developments, uses must follow the RRD’s Google AI Acceptable Use Guide, Client AI Restrictions & any other IT related policy.
