experience. Leading a team of approximately 20 highly skilled data scientists and machine learning practitioners, this leader provides deep technical direction

across production AI systems including conversational virtual agents, real-time

agent assist, and intelligent routing. Beyond delivery, the role serves as the

organization's AI thought leader—continuously evaluating emerging technologies, foundation models, agent architectures, and vendors to shape a three-year technology roadmap and build-versus-buy strategy. The role partners with Product and Engineering to deliver production AI systems while establishing best practices for AI evaluation, LLMOps, governance, and responsible AI. Success is measured by customer outcomes, agent productivity, sales enablement, operational efficiency, and the long-term technical health of the AI platform.

ESSENTIAL JOB SKILLS/DUTIES

• Define the long-term AI technology vision and three-year roadmap across

virtual agents, agent assist, and intelligent routing, including build-versus-buy

decisions.

• Provide technical leadership and mentorship to a team of 20 experienced data

scientists and ML/GenAI practitioners, raising engineering and scientific rigor.

• Lead AI architecture decisions spanning LLMs, RAG, agentic AI, evaluation

frameworks, orchestration, and production deployment.

• Drive customer-facing virtual agents that gather information, resolve issues,

detect sentiment, avoid hallucinations, and seamlessly escalate with full

conversational context.

• Deliver real-time AI agent assist capabilities including knowledge retrieval,

next-best action, desktop guidance, call summarization, and sales recommendations.

• Develop predictive routing and decision intelligence that matches customers to the optimal resource using intent, history, agent skills, and business outcomes.

• Establish standards for AI evaluation, hallucination mitigation, observability,

LLMOps, Responsible AI, and continuous experimentation.

• Continuously evaluate emerging AI research, vendors, and platforms to ensure

Asurion adopts scalable technologies and avoids dead-end architectures.

• Represent Asurion externally through industry events, technical conferences,

and thought leadership while building relationships across the AI ecosystem.

REQUIRED TECHNICAL SKILLS

• Deep expertise in Large Language Models (LLMs), agentic AI, conversational AI, and voice AI.

• Production experience with RAG, prompt engineering, AI evaluation, guardrails,

hallucination mitigation, and LLMOps.

• Strong background in machine learning, predictive modeling, optimization,

recommendation systems, and intelligent routing.

• Experience evaluating foundation models and AI vendors and making build-

versus-buy technology recommendations.

• Cloud AI platforms and modern AI frameworks.

• Production AI architecture, experimentation, monitoring, and governance.

REQUIRED LEADERSHIP SKILLS

• Recognized technical thought leader with the ability to communicate complex

AI concepts to executives, customers, and industry audiences.

• Technical coaching and mentorship for senior data scientists and ML practitioners.

• Strategic technology planning and architectural decision making.

• Cross-functional influence with Product and Engineering organizations.

• Executive presence and public speaking at conferences and customer events.

REQUIRED EDUCATION & EXPERIENCE

• Advanced degree in Computer Science, AI, Machine Learning, Statistics, or

related field, or equivalent experience.

• 12+ years leading applied AI, machine learning, or data science teams delivering production systems.

• Experience defining enterprise AI strategies and technology roadmaps.

• Experience partnering with software engineering organizations to deploy AI

products at scale.

PREFERRED EDUCATION & EXPERIENCE

• PhD or Master's in AI, Computer Science, Machine Learning, or related

discipline.

• Experience leading AI organizations within product development environments.

• Recognized contributions to the AI community through publications, conference presentations, open-source projects, or industry leadership.

PREFERRED LICENSES/CERTIFICATIONS

• AI/ML certifications from major cloud providers or leading AI platforms.

• Demonstrated expertise in production AI, LLMOps, or Responsible AI

frameworks.