Agentic AI in Contact Center

Role purpose:

The Product & Technical Expert (PTE) leads and manages the product and technical tasks of the Agentic AI in Contact Center project across its three components — the virtual AI bot/conversational IVR, the agent-assist, and interaction analytics. The role spans requirements and vendor selection through solution design, integration, AI governance, and delivery oversight, while building lasting in-house capability through knowledge transfer to a nominated internal candidate.

Key responsibilities:

Manage and refine the business and technical requirements across the three components (virtual AI bot/conversational IVR, the agent-assist, and interaction analytics), and maintain the requirements and compliance matrices.

Build and maintain the use-cases and intent-prioritization backlog (Tier 1 automated, Tier 2 AI-assisted, Tier 3 human), translating call-driver data into an automation roadmap.

Define KPIs and success/acceptance criteria.

Support RFP issuance, run the technical evaluation of bidders, lead proofs-of-concept (including Saudi-dialect quality testing), and make sourcing recommendations.

Manage the implementation partner technically — scope, statement of work, deliverables, and quality.

Manage the conversational and agentic design: open intent capture, dialog flows, prompts, tone/persona, escalation triggers, and warm-handoff behavior.

Manage the design of RAG grounding approach, knowledge-base structure, and guardrail configuration.

Define the target architecture and external/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.

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

Establish the AI governance and guardrail framework aligned to SAMA and PDPL — human-in-the-loop for sensitive flows, audit trail, data residency, and PII redaction.

Work with Compliance, Risk, Legal, and Information Security to secure the necessary approvals.

Manage SIT, UAT, and phased go-live; manage risks, issues, and dependencies.

Stand up the analytics/AI-ops monitoring and reporting, and run the post-go-live.

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