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Run Regional ABM/ABX for AECO and Government accounts across ANZ: build account plans with AEs, adapt global campaigns to local accounts, act on 6Sense intent signals, own field events and budgets, coordinate BDR/SDR outreach, and feed buyer insights back to global marketing to drive pipeline and close deals.

Produce B2B content across the funnel—landing pages, emails, social, thought leadership, webinars, and video scripts. Lead AI-assisted content creation, collaborate with Growth, Creative, Sales, and agencies, and use SEO, Google Analytics, and CMS to optimize performance.

Own on-time, in-scope delivery for technical SaaS programs. Act as Product Owner for a development team, translate product needs into technical requirements, manage risks and dependencies, run Agile ceremonies, and align stakeholders while driving process improvements and delivery frameworks.

Manage a large mid-market and enterprise SaaS portfolio to drive onboarding, adoption, renewals, retention, and growth. Identify churn risks and upsell opportunities, maintain account data in Salesforce, collaborate cross-functionally with Sales, Support, and Customer Experience, and cultivate customer advocacy to maximize lifetime value.

Lead strategy and hands-on administration of the martech stack (Marketo, 6Sense, Salesforce, AI SDRs). Build and maintain integrations, diagnose and resolve data and sync issues, design campaign logic, collaborate with RevOps and Data, set the martech roadmap, and translate technical details for stakeholders to convert platform capability into pipeline and revenue.

Lead global go-to-market campaign strategy for a vertical: set campaign architecture, define messaging and buyer journeys, partner cross-functionally, own measurement and pipeline performance, and enable regional activation.

Lead end-to-end digital campaign delivery across LinkedIn, Google Ads, programmatic, email, events, webinars, and ABM. Manage agencies, ensure tracking/UTM and Salesforce mapping, analyze funnel and attribution, optimize for pipeline, and report performance to stakeholders.

The role involves designing scalable ML infrastructure, managing Kubernetes platforms, building ML tools, and ensuring production system reliability.

Build and operate scalable ML infrastructure and LLM platforms: large-scale batch inference on Kubernetes, real-time model serving, GPU-distributed training, CI/CD and developer experience, observability and SLAs, production Python libraries, vendor integrations, and tech-lead responsibilities across ML teams.