AI Automation Analyst (Claude)

End-to-End AI Strategy: Own and manage AI automation initiatives across the entire Customer Experience (CX) lifecycle, from onboarding and adoption to renewals.

Claude Workflow Engineering: Design, build, and deploy sophisticated Claude-based workflows to automate customer intelligence, health scoring, and repetitive CX processes.

Revenue Orchestration: Automate the integration of customer insights into core business drivers, including renewals, upsells, and cross-sell opportunities.

AI Insight Extraction: Develop automated frameworks for high-level data synthesis, including NPS analysis, churn patterns, and insight extraction from customer interactions.

Prompt Engineering Leadership: Create and maintain scalable prompt engineering frameworks and reusable templates to ensure the consistency and accuracy of AI outputs.

Cross-Functional Integration: Collaborate with Product, Sales, and Ops to seamlessly integrate AI workflows into existing tech stacks, including CRMs and support platforms.

QA & Brand Governance: Establish rigorous quality assurance processes to validate AI outputs for compliance, accuracy, and alignment with the corporate brand voice.

Performance Optimization: Monitor and tune automation performance against key business metrics such as NRR (Net Revenue Retention), Retention Rate, and CSAT.

Enablement & Governance: Act as the internal Subject Matter Expert (SME) for AI capabilities, providing documentation, stakeholder training, and ensuring responsible AI data privacy and risk mitigation.

Education: Bachelor’s degree in Business, Analytics, Computer Science, or a related technical field (Master’s in AI/ML preferred).

Core Experience: 2–4 years of proven success in CX operations, AI automation, or high-level data analytics.

LLM Proficiency: Hands-on experience with Claude or other LLMs, including a strong background in prompt engineering and workflow design.

Tech Stack Expertise: Familiarity with core CX platforms and integrations, including Salesforce, Pendo, Slack, and automation tools like Zapier.

Systems Thinking: Strong analytical ability to translate complex business problems into scalable, automated AI solutions.

Technical Literacy: Solid understanding of APIs, data integrations, and the infrastructure required for seamless AI workflow deployment.

Strategic Communication: Excellent ability to explain technical AI capabilities, limitations, and governance to non-technical stakeholders.

Operational Rigor: Demonstrated skill in balancing rapid execution with high-quality output, thorough documentation, and risk mitigation.