Conversational AI Manager

Overview

As Conversational AI Manager, you own the live AI agent’s performance and weekly improvement, ensuring high-quality client interactions. You collaborate with a platform partner to implement capabilities while maintaining end-to-end accountability for live service. You drive optimization, experimentation, and regulatory-compliant automated decisions, shaping how IG serves clients through AI-powered channels. This role blends hands-on analytics with vendor collaboration to deliver measurable impact in a high-volume, regulated environment.

Pay / Benefits

• competitive salary
• Flexible Benefits Package (12%)
• Private medical cover
• Life insurance
• Gym membership contributions
• 25 days holiday (+1 Birthday, +2 voluntary work days)

Responsibilities

• Own live performance of the AI agent, tracking resolution rate and CSAT on every change
• Manage the ongoing optimisation roadmap with a weekly, evidence-driven backlog
• Diagnose underperformance using own case analysis and adviser insights rather than relying solely on partner reports
• Build and run experimentation with hypotheses, metrics, sample sizes, stopping rules, and tangible decision-changing results
• Ensure implementations remain compliant with the relevant regulatory framework
• Own eligibility rules and confidence thresholds for automated decisions and justify to Compliance if needed
• Act as the platform partner’s primary counterpart, holding them to delivery timelines and escalating when necessary
• Take ownership of each new capability at go-live, setting client requirements and accuracy standards beforehand

Key requirements

• Track record of owning a conversational AI service in a high-volume regulated environment with measurable results
• Experience managing a delivery partner and maintaining a working relationship under commitments
• Hands-on experimentation on live client journeys with proper sample sizing and data-backed decisions
• Data-led approach with comfort in contact analytics, measurement design and root-cause analysis
• Product management craft: outcome ownership, prioritisation by value, backlog discipline, in-life iteration
• Enough technical fluency to discuss API returns and push back on designs
• Awareness of IG’s regulatory context, including Consumer Duty and needs of vulnerable clients in automated decisions

• data-driven decision making
• strong stakeholder management
• problem-solving under regulatory constraints
• conversational AI
• data analytics and measurement design
• root-cause analysis

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