AI Integration Lead: Customer Success

Department: Customer Success

Location: SA | Central | Remote

Description

The AI Integration Lead: Customer Success is responsible for leveraging AI to enhance the customer journey and improve internal efficiencies across the company. This role will focus on using AI to proactively resolve customer inquiries, streamline support processes, and drive commercial improvement. The AI Integration Lead: Customer Success will play a crucial role in defining strategies for AI integration within customer success operations, ensuring that AI technologies are utilized to optimize customer experiences and operational productivity.

Key Responsibilities

• Lead the integration of AI technologies into customer success operations.
• Develop and implement AI-driven solutions to proactively resolve customer inquiries.
• Define strategies for using AI to enhance internal efficiencies and streamline support processes.
• Collaborate with cross-functional teams to translate AI insights into business value.
• Mentor and lead a team focused on AI-driven customer success initiatives.
• Drive commercial improvement through AI-enhanced customer journey strategies.
  
  
  

Skills, Knowledge and Expertise

Qualifications Required

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• PhD in a relevant field is a plus.

Experience Required

• 5+ years of experience in AI, machine learning, or data science roles, with a focus on customer success or support.
• Proven track record of driving operational improvements and cost reductions within a software organization.
• Experience in leading and mentoring teams focused on AI initiatives.
• Familiarity with customer success operations and commercial improvement strategies.
  
  

Skills and Knowledge Required

• Proficiency in programming languages such as Python, R, or Java.
• Deep understanding of machine learning, deep learning, and other AI techniques.
• Experience with AI-driven customer support tools and frameworks.
• Strong knowledge of cloud computing platforms and MLOps practices.