Agentic AI in Contact Center

About the Role
The Product & Technical Expert (PTE) leads and manages the product and technical tasks of the Agentic AI in Contact Center project, which encompasses three key components: the virtual AI bot/conversational IVR, agent-assist, and interaction analytics. This role is responsible for overseeing the entire project lifecycle, including requirements gathering, vendor selection, solution design, integration, AI governance, and delivery oversight. In addition, the PTE will build lasting in-house capabilities through effective knowledge transfer to a designated internal candidate.

Key Responsibilities

• Manage and refine business and technical requirements for the virtual AI bot/conversational IVR, agent-assist, and interaction analytics, while maintaining requirements and compliance matrices.
• Build and maintain use-cases and intent-prioritization backlog (Tier 1 automated, Tier 2 AI-assisted, Tier 3 human), translating call-driver data into an actionable automation roadmap.
• Define KPIs and success/acceptance criteria.
• Support the issuance of RFPs, conduct technical evaluations of bidders, lead proofs-of-concept (including tests for Saudi dialect quality), and make sourcing recommendations.
• Technically manage the implementation partner, including scope, statement of work (SOW), deliverables, and quality assurance.
• Oversee the conversational and agentic design elements: open intent capture, dialog flows, prompts, tone/persona, escalation triggers, and warm-handoff behavior.
• Design the approach for RAG grounding, knowledge-base structure, and guardrail configuration.
• Specify target architecture and external/internal integration design for core banking (T24), CRM (MS Dynamics), Cortex, e-channels, OTP, and the Cisco IVR/ACD and speech-recording stack.
• Define APIs, real-time context retrieval, latency targets, and model-hosting approaches.
• Provide advisory on model selection (LLM/SLM and routing), RAG techniques, hallucination mitigation, confidence thresholds, and prompt/version management.
• Establish the AI governance and guardrail framework aligned with SAMA and PDPL requirements, including recommendations for a human-in-the-loop for sensitive flows, audit trails, data residency, and PII redaction.
• Collaborate with Compliance, Risk, Legal, and Information Security teams to secure necessary approvals.
• Manage System Integration Testing (SIT), User Acceptance Testing (UAT), and phased go-live implementations while overseeing risks, issues, and dependencies.
• Implement AI-operations monitoring and reporting post-go-live, addressing any ongoing operational needs.
• Coach and up-skill the nominated internal candidate (prospective AI-Ops Lead) as well as the wider team; produce runbooks and facilitate operational handover.