Senior Product Operations Manager – LLM Automation

Responsibilities:
Own the contact-centre deflection roadmap. Translate operational pain points (volume peaks, repeat queries, cost drivers) into a prioritised intent-automation roadmap, measuring success by deflection rate, cost per interaction, and customer satisfaction — not feature counts. Design and own the intent taxonomy and evaluation framework. Build the classification hierarchy underpinning every agent, establish pass-rate-by-intent metrics and confusion matrices, and instrument the hard distinction between containment (agent solves it) and deflection (client doesn't contact us) across live and shadow traffic. Drive LLM agent deployment and iteration cycles. Partner with Engineering to ship agents to production, own go/no-go decisions using multi-metric eval gates (accuracy thresholds, containment rates, customer sentiment, compliance risk), and write PRDs that survive legal and engineering scrutiny simultaneously. Navigate multilingual evaluation complexity. Oversee agent performance across 15+ languages and five regulatory jurisdictions; distinguish genuine linguistic gaps from regulatory differences or domain drift, and prioritise fixes accordingly. Drive cross-functional consensus under conflicting incentives. Hold the conversation where Customer Success demands safety-first, Engineering wants velocity, Compliance requires audit trails, and Exec needs the headline number. Document decisions in ADRs that explain the trade-off, not just the conclusion — own closure, not consensus theatre. Build and maintain regulatory evidence packs. Produce documentation that satisfies FCA Consumer Duty obligations, EU AI Act high-risk categorisation assessments, and internal governance — showing that your agents classify intent accurately, don't discriminate, and degrade gracefully under uncertainty. Author high-bar product artefacts. Produce PRDs, ADRs, exec memos, and board briefing materials that survive scrutiny from product, legal, finance, and regulators. Your written output is evidence. Establish and challenge your own reasoning. Distinguish first-principles analysis from market heuristics, run pre-mortems, and quote uncertainty explicitly. Act when you can test; defer when you can't.

Requirements:
5+ years in product roles owning customer-operations or contact-centre automation — accountable for deflection outcomes, measuring cost per interaction, and iterating on actual operational metrics, not just "worked on a support project". Proven track record of shipping and measuring cost/deflection outcomes, speaking in outcomes (cost reduction, containment, customer friction) rather than outputs (calls handled). Intent taxonomy and eval design fluency — reading confusion matrices, distinguishing accuracy from containment, and designing holdout test sets and eval gates ahead of production deployment. Comfort in regulated environments (FCA, CySEC, ASIC, SCB, CMA) — able to discuss Consumer Duty, vulnerable-customer treatment, AI governance, and data governance with compliance teams without a translator. Demonstrated ability to ship LLM/AI agents to production, including awareness of the gap between lab and live performance, latency, token costs, and hallucination surfaces. Cross-functional decision closure under conflicting incentives — you produce ADRs that explain a trade-off and a decision, not consensus documents, and you're comfortable saying no. High written-output bar — PRDs, ADRs, and exec memos that separate fact from assumption, quote confidence levels, and survive scrutiny from lawyers, CFOs, and product leaders. Calibrated reasoning and first-principles thinking — you distinguish market heuristics from a reasoned case for action and quote your confidence explicitly.