Jobs at splose

Run standardized, high-volume onboarding for mid-market customers (15–49 practitioners). Enforce self-serve data templates, manage data migrations, escalate complex issues to engineering, capture friction patterns for process improvement, and promote upsell features like SMS and Stripe while maintaining SLA-driven, consistent customer experiences.

First-line live chat support for UK clients using Splose; troubleshoot product issues, log and track tickets, escalate bugs to product/engineering, maintain knowledge base, and collaborate with Customer Success to protect client experience and CSAT.

Provide frontline chat-based support for a SaaS practice management platform, handling billing and subscription enquiries, first-level technical troubleshooting, coordinating small business data imports, meeting SLAs, surfacing product issues to internal teams, and contributing to process and documentation improvements to boost customer satisfaction.

Drive outbound prospecting and manage the full sales cycle to acquire new business for splose's practice management SaaS. Qualify leads, run product demos, build and maintain pipeline, collaborate on sales strategy, and meet or exceed revenue targets while leveraging existing relationships.

Lead post-sale functions across ANZ and the UK, owning onboarding, support, renewals, expansion, revenue retention, customer health scoring, advocacy, and cross-functional feedback to shape product and commercial strategy.

Generate and qualify new business opportunities via inbound lead management and outbound prospecting. Conduct cold calls, email outreach and social selling, schedule qualified meetings for Account Executives, maintain CRM records, research target accounts, meet activity and pipeline targets, and collaborate with Sales and Marketing to improve lead quality.

Perform high-volume outbound prospecting (calls, email, social) to build a pipeline of qualified meetings for Account Executives. Research accounts, identify decision makers, record activity in CRM, meet activity and pipeline targets, collaborate with marketing and AEs, and participate in training and coaching.

Lead the AI product strategy for clinical notes and documentation, defining roadmap and shipping LLM-powered features from 0 to 1. Partner with Engineering, Data, Design, and clinical SMEs to select models, design prompts, optimize inference pipelines, and build evaluation frameworks. Prioritise clinician trust, quality, cost-efficiency, user experience, and measurable metrics (adoption, quality, performance). Drive customer research and cross-functional alignment to scale safe, accurate AI features.