Jobs at Dialpad

Leads global and national partner marketing programs for Google Cloud and T-Mobile, driving partner engagement, pipeline, and revenue. Develops joint go-to-market strategies, integrated campaigns, seller enablement, executive and customer events, advocacy programs, and scalable co-marketing frameworks. Manages MDF budgets, establishes performance KPIs, measures ROI, and optimizes partner marketing processes. Collaborates with Channel Sales, strategic partners, executives, and cross-functional teams to translate cloud, AI, and platform capabilities into compelling customer and seller programs.

Own end-to-end enterprise customer deployments from kickoff through launch and adoption. Manage project plans, scope, timelines, milestones, risks, dependencies, deliverables, escalations, and changes across multiple implementations. Lead customer meetings, executive communications, administrator training, integrations, device provisioning, and issue resolution. Partner with Solution Architects, Customer Success, Support, Product, Sales, and other teams to deliver successful SaaS implementations and transition customers into long-term adoption.

Lead platform-level product design, define patterns and primitives, build AI-first capabilities, ship coded prototypes and production code, evolve the design system, mentor designers, and improve cross-team design practices to scale Dialpad's AI-native product.

Manage a portfolio of mid-market customers to grow ARR through consultative account management, pipeline generation, territory planning, cross-sell/expansion, forecasting, and customer advocacy. Collaborate with sales, CS, PS, and partners to meet quarterly revenue targets and ensure customer value and satisfaction.

Dialership is a virtual, unpaid summer program (June–August 2027) where participants attend two weekly sessions to learn about business functions (sales, engineering, marketing, product, AI, etc.), network with leaders, get resume/LinkedIn feedback, and receive a certificate upon completion. No work projects are assigned; participants commit to 2 hours/week and engage in interactive sessions.

Design, build, evaluate, deploy, and stabilize customer-specific AI agents in production. Translate business workflows into technical solutions, implement enterprise integrations, develop evaluation and safety controls, tune performance, lead go-live and hypercare, and document reusable deployment practices. Collaborate with customers, Product, Engineering, and delivery teams to improve agent reliability, operational effectiveness, and measurable business outcomes.