About the role

AI Automation Analyst managing Claude-based workflows for customer experience in a finance tech company. Drive automation initiatives and integrate insights across customer lifecycle.

Responsibilities

Own and manage AI automation initiatives across the entire Customer Experience (CX) lifecycle, from onboarding and adoption to renewals.
Design, build, and deploy sophisticated Claude-based workflows to automate customer intelligence, health scoring, and repetitive CX processes.
Automate the integration of customer insights into core business drivers, including renewals, upsells, and cross-sell opportunities.
Develop automated frameworks for high-level data synthesis, including NPS analysis, churn patterns, and insight extraction from customer interactions.
Create and maintain scalable prompt engineering frameworks and reusable templates to ensure the consistency and accuracy of AI outputs.
Collaborate with Product, Sales, and Ops to seamlessly integrate AI workflows into existing tech stacks, including CRMs and support platforms.
Establish rigorous quality assurance processes to validate AI outputs for compliance, accuracy, and alignment with the corporate brand voice.
Monitor and tune automation performance against key business metrics such as NRR (Net Revenue Retention), Retention Rate, and CSAT.
Act as the internal Subject Matter Expert (SME) for AI capabilities, providing documentation, stakeholder training, and ensuring responsible AI data privacy and risk mitigation.

Bachelor’s degree in Business, Analytics, Computer Science, or a related technical field (Master’s in AI/ML preferred).
2–4 years of proven success in CX operations, AI automation, or high-level data analytics.
Hands-on experience with Claude or other LLMs, including a strong background in prompt engineering and workflow design.
Familiarity with core CX platforms and integrations, including Salesforce, Pendo, Slack, and automation tools like Zapier.
Strong analytical ability to translate complex business problems into scalable, automated AI solutions.
Solid understanding of APIs, data integrations, and the infrastructure required for seamless AI workflow deployment.
Excellent ability to explain technical AI capabilities, limitations, and governance to non-technical stakeholders.
Demonstrated skill in balancing rapid execution with high-quality output, thorough documentation, and risk mitigation.