AI Customer Experience Technical Advisor

AI Customer Experience Technical Advisor

(Technical Business Analyst – Contact Center AI)

Department: Technical Source’s SaaS Client – Professional Services / Customer Experience
Location: Remote / US-Based
Role Level: Senior / Lead Individual Contributor

About the Role

The AI Customer Experience Advisor is a hybrid role that combines the analytical rigor of a technical business analyst, the systems thinking of an engineer, the customer-facing presence of a sales professional, and the curiosity of a detective. This position exists to solve complex customer problems in highly ambiguous environments by uncovering how the customer's contact centers operates today and translating that insight into a prioritized, engineered AI-driven customer experience platform for future state CX efficiency and cost savings.

This advisor works directly with customers to investigate their current-state contact center operations—how interactions flow, where volume originates, how agents spend their time, and what matters most to the business. Through structured discovery, data analysis, and consultative dialogue, the advisor extracts what is most critical to the customer and connects those priorities to the practical capabilities of modern CX AI tools, AI Bots, Chat Bots. and Client Agents.

The role requires both technical depth and business fluency: the ability to understand AI and contact center technologies at a functional level while clearly articulating their value in business terms. The outcome is a custom, phased AI implementation strategy that replaces or augments routine interactions, enabling Hybrid Agents to focus on complex, high-value customer issues and delivering the best possible customer experience.

Key Responsibilities

Investigative Discovery & Customer Problem Solving

• Act as a “detective” to uncover the customer’s true current state, even when documentation, data, or clarity is limited.
• Lead customer discovery sessions to understand contact center workflows, interaction drivers, call and digital volume patterns, and agent utilization.
• Identify which contact center tasks are most important to the customer based on business impact, customer friction, and operational cost.
• Distill complex, ambiguous information into clear problem statements and prioritized opportunities.
• There is a heavy emphasis on AI, AI Bots, AI Chat and Client Agent implementation background. Candidates must have an engineering level understanding of how these systems are engineered, implemented and understanding of what they do best and what the limitations of these tools are and be able to work with customers to advise them on implementation strategies.

Technical Business Analysis & AI Capability Mapping

• Serve as the technical business analyst between customer stakeholders and engineering/delivery teams.
• Analyze current systems, workflows, and data readiness to determine where AI tools can be applied most effectively.
• Understand the functional capabilities and constraints of AI tools within the new contact center platform.
• Map customer needs to AI capabilities, clearly identifying what should be automated, augmented, or left to human agents.
• Prioritize AI implementations based on customer value, technical feasibility, and operational impact.

Solution Strategy & Custom Platform Engineering

• Design phased implementation strategies that align AI capabilities to customer priorities and readiness.
• Partner with engineering and delivery teams to translate business requirements into technical solution designs.
• Ensure AI solutions are engineered to integrate seamlessly into existing contact center workflows.
• Guide customers toward Hybrid Agent models where AI replaces repetitive tasks and humans focus on complex customer interactions.
• Validate solution designs against customer goals for accuracy, containment, escalation, and customer satisfaction.

Customer Engagement & Value Communication

• Engage customers with the confidence and clarity of a sales professional, building trust and credibility at all levels of the organization.
• Translate technical capabilities into clear business value, helping customers understand why certain AI tools matter more than others.
• Align executive, operational, and technical stakeholders around a shared AI roadmap and success criteria.

Implementation Partnership & Optimization

• Provide consultative oversight throughout discovery, design, testing, UAT, and go-live.
• Review customer interaction data to validate AI performance and identify optimization opportunities.
• Collaborate with internal teams to manage risks, dependencies, and design trade-offs.
• Help customers measure success using KPIs such as containment, deflection, CSAT, FCR, and agent productivity.

Qualifications

Required

• 5+ years of experience in customer experience, contact center operations, business analysis, AI/automation, or professional services consulting.
• Proven ability to operate as a technical business analyst in customer-facing environments.
• Engineering mindset with the ability to understand systems, workflows, and technical trade-offs.
• Strong customer-facing communication skills comparable to a sales or solutions consulting role.
• Demonstrated ability to extract critical insights from ambiguous or incomplete customer information.
• Experience analyzing contact center data, interaction volumes, and operational workflows.
• Ability to prioritize and align AI capabilities to real customer needs and business outcomes.
• Familiarity with CX metrics such as containment, CSAT, FCR, AHT, and digital deflection.

Preferred

• Experience with CCaaS platforms, Virtual Agents, or AI-assisted agent tools.
• Knowledge of conversational UX, prompt engineering, or knowledge management strategy.
• High-level understanding of APIs, integrations, and data flows.
• Experience supporting phased or iterative platform implementations.

What Success Looks Like

• Customers gain clarity on how their customers' contact center operates today and how AI features within a contact center platform can be adopted to build efficiencies and cost savings to the customer post sale.
• Tasks within the contact center are identified and prioritized with confidence to be replaced by AI BOT or AI Agents to save time and cost.
• AI capabilities are mapped and implemented based on customer value, not assumptions.
• Custom AI-powered contact center platforms are engineered to support Hybrid Agent models.
• Customers experience measurable improvements in efficiency, customer satisfaction, and agent effectiveness.
• Internal teams view the Advisor as a trusted technical problem solver and customer advocate.