Conversational AI Manager
City of London - United Kingdom, UK
Key offer highlights
Full-time
Onboarding training
Description
IG Group is a FTSE 100 fintech operating across five continents, serving over 1.4m customers and handling billions of dollars in transactions – built on scale, trust, and proof. We didn't pivot to innovation; it's how we've always operated. What that means for the people who work here is real: genuinely complex problems to solve, the technology and resources to tackle them properly, and the kind of scope that's rare in
The perks:
Competitive salary
Flexible Benefits Package on top of your salary (12%)
Private medical cover for you and your family
Life insurance
Contribution to gym memberships
25 Days holiday, with 1 additional day off to celebrate your Birthday & 2 additional days off a year for voluntary work (28 in total)
The option to buy or sell holiday days
A comprehensive global and local onboarding process
Enhanced primary (maternity), secondary (paternity), and shared parental pay and leave, as well as a range of support and benefits for parents
What success looks like
Optimisation runs as a weekly rhythm rather than a series of reactions, with a backlog that always holds the next evidenced change
Experiments land on a regular cadence and have changed decisions, including at least one change killed because the data did not support it
Every live threshold has a justification you can give from memory, and the escalation and challenge routes have survived audit scrutiny
The platform partner treats you as the decision-maker and is candid about problems rather than defensive
What you’ll need:
A track record of owning a conversational AI service, in a high-volume regulated environment, with results you can speak to precisely: the baseline, what changed, and how it was proven
Experience managing a delivery partner you depended on for execution, where you held someone to a commitment and kept the relationship intact
Hands-on experimentation on live client journeys: sizing samples in advance and having abandoned your own idea when the numbers did not support it
A data-led approach: comfortable in contact analytics, measurement design and structured root-cause analysis, and hard to sell to
Product management craft: outcome ownership, prioritisation by value, backlog discipline, in-life iteration
Enough technical fluency to be a peer to an engineering-minded manager: you can discuss what an API can realistically return and push back on a proposed design
Awareness of IG’s regulatory context, including Consumer Duty outcomes and the needs of vulnerable clients, in how automated decisions are designed and measured
What you'll do:
Own live performance: resolution rate is our primary metric with repeat contact and journey CSAT tracked on every change, so removed contact is a solved problem rather than a displaced one.
Own the ongoing optimisation roadmap: a prioritised backlog of configuration changes and new procedures, sequenced weekly and defended on evidence
Diagnose underperformance to root cause using your own case sampling, referred and declined case analysis, complaint themes and advisor insight, rather than the partner’s reporting alone
Build and run the experimentation practice: hypotheses, primary and guardrail metrics, sample sizes set before launch, stopping rules, and results that actually change what we do
Ensure any implementations are/remain compliant with the relevant regulatory framework
Own and confirm the eligibility rules and confidence thresholds applied to automated decisions, and justify to Compliance if required.
Act as the platform partner’s primary counterpart holding them to committed delivery timelines and escalating within their organisation when work is not moving
Take ownership of each new capability at go-live, having set the client requirements and accuracy standards for it before build started