Description

Key Responsibilities

• Architect and deliver end-to-end AI and Generative AI solutions supporting Contact Center and Customer Experience (CX) organizations.
• Design and implement intelligent virtual agents, AI-powered agent assist capabilities, knowledge management solutions, and automated customer interaction workflows.
• Develop RAG-based applications, conversational AI platforms, multi-agent systems, and LLM-powered customer support solutions.
• Partner with Contact Center leaders, operations teams, and business stakeholders to identify opportunities for AI-driven automation and process optimization.
• Create AI solutions to improve call deflection, first-call resolution, customer sentiment analysis, agent productivity, quality monitoring, and root cause analysis.
• Design scalable cloud architectures supporting high-volume customer interactions across voice, chat, email, and digital channels.
• Lead development of predictive analytics models for customer behavior, churn prediction, workforce planning, and operational forecasting.
• Establish AI governance, MLOps frameworks, model monitoring, and responsible AI best practices.
• Collaborate with engineering teams to develop streaming and batch data pipelines supporting real-time customer engagement use cases.
• Present solution architectures, business cases, and AI transformation strategies to executive and senior leadership teams.
• Create reference architectures, technical standards, and implementation roadmaps for enterprise AI adoption.
• Provide technical leadership and mentorship to data scientists, engineers, architects, and business teams.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related technical discipline.
• 10+ years of experience in AI/ML, Solution Architecture, Data Analytics, Cloud Architecture, or Customer Experience technologies.
• Proven experience architecting and deploying enterprise AI and Generative AI solutions.
• Experience supporting Contact Center, Customer Experience, Customer Service, or Customer Operations organizations.
• Strong understanding of customer service workflows, knowledge management, conversational AI, and customer engagement strategies.
• Experience designing solutions utilizing LLMs, RAG architectures, Agentic AI, and conversational AI technologies.
• Hands-on experience with machine learning frameworks and cloud AI services.
• Experience working with executive stakeholders and driving large-scale digital transformation initiatives.
• Strong communication and stakeholder management skills.

Preferred Qualifications

• Experience with Contact Center platforms such as Genesys, NICE CXone, Five9, Amazon Connect, Cisco Contact Center, or similar technologies.
• Google Cloud Professional Machine Learning Engineer certification or equivalent cloud certification.
• Experience implementing AI-powered agent assist, quality monitoring, call summarization, or customer analytics solutions.
• MBA or advanced degree focused on Business Analytics, Data Science, Innovation, or Technology Management.
• Experience within telecommunications, customer service, customer operations, or enterprise technology environments.

Technical Skills

AI & Generative AI

• Generative AI.
• Large Language Models (LLMs).
• Retrieval-Augmented Generation (RAG).
• Agentic AI.
• Multi-Agent Systems.
• Prompt Engineering.
• Conversational AI.
• Intelligent Virtual Agents.
• LangChain.
• Vertex AI.
• TensorFlow.
• PyTorch.
• AutoML.
• MLOps.

Contact Center & Customer Experience

• AI Agent Assist.
• Contact Center Automation.
• Customer Sentiment Analysis.
• Call Summarization.
• Knowledge Management.
• Customer Journey Analytics.
• Workforce Optimization.
• Conversational Analytics.
• Quality Monitoring.
• Customer Self-Service Solutions.

Data & Analytics

• Apache Spark.
• SQL.
• BigQuery ML (BqML).
• Tableau.
• Power BI.
• Looker.
• Alteryx.
• Predictive Analytics.
• Real-Time Data Processing.

Cloud & Development

• Google Cloud Platform (GCP).
• Python.
• SQL.
• R.
• Docker.
• CI/CD Pipelines.
• API Integrations.
• Data Engineering

Key Skills

Education

Bachelor's degree