Agentic AI in Contact Center

Role Overview

Product & Technical Expert (PTE) for Agentic AI in Contact Center at TAWANTECH. This role leads and manages the product and technical delivery of a three-component AI initiative spanning virtual AI bot / conversational IVR, agent-assist, and interaction analytics.

Role Purpose

Lead and manage all product and technical tasks of the Agentic AI in Contact Center project from requirements and vendor selection through solution design, integration, AI governance, and delivery oversight. Build lasting in-house capability through structured knowledge transfer to a nominated internal candidate.

Key Responsibilities

Requirements & Backlog Management

• Manage and refine business and technical requirements across all three components (virtual AI bot / conversational IVR, agent-assist, and interaction analytics).
• Maintain the requirements and compliance matrices.
• Build and maintain the use-cases and intent-prioritization backlog, structured as Tier 1 automated, Tier 2 AI-assisted, and Tier 3 human.
• Translate call-driver data into an automation roadmap.
• Define KPIs and success and acceptance criteria.

Vendor Selection & Procurement

• Support RFP issuance and run technical evaluation of bidders.
• Lead proofs-of-concept, including Saudi-dialect quality testing.
• Make sourcing recommendations.

Implementation & Delivery Management

• Manage the implementation partner technically across scope, statement of work, deliverables, and quality.
• Manage SIT, UAT, and phased go-live activities.
• Manage risks, issues, and dependencies throughout delivery.

Conversational & Agentic Design

• Manage conversational and agentic design including open intent capture, dialog flows, prompts, tone and persona definition, escalation triggers, and warm-handoff behavior.
• Manage the design of RAG grounding approach, knowledge-base structure, and guardrail configuration.

Architecture & Integration

• Define the target architecture and external and internal integration design across core banking (T24), CRM (MS Dynamics), Cortex, e-channels, OTP, and the Cisco IVR / ACD and speech-recording stack.
• Specify APIs, real-time context retrieval, latency targets, and the model-hosting approach.

AI Model & Technology Strategy

• Advise on model selection (LLM / SLM and routing), RAG, hallucination mitigation, confidence thresholds, and prompt and version management.

AI Governance & Compliance

• Establish the AI governance and guardrail framework aligned to SAMA and PDPL requirements.
• Implement human-in-the-loop controls for sensitive flows, audit trail, data residency, and PII redaction.
• Work with Compliance, Risk, Legal, and Information Security to secure necessary approvals.

Monitoring & Operations

• Stand up the analytics and AI-ops monitoring and reporting.
• Run post-go-live operations and optimization.

Knowledge Transfer & Capability Building

• Coach and up-skill the nominated internal candidate (prospective AI-Ops Lead) and the wider team.
• Produce runbooks and operational handover documentation.