Opportunities in NYC, United States

ABOUT THE ROLE We’re hiring a Sales Development Representative (SDR) to generate qualified pipeline through outbound prospecting and inbound follow-ups. As an early non-engineering hire, you’ll help shape our go-to-market motion and messaging, and play a fundamental role in onboarding potential customers. WHAT YOU’LL DO

• Prospect & outreach: Identify and engage target accounts via email, LinkedIn, cold calling, organizing events (led by you), and attending conferences.
• Qualify & coordinate: Run first-call discovery, identify decision makers, book meetings for AEs, and identify potential use cases for prospects.
• Build relationships: Nurture champions and connect with decision makers. ABOUT YOU
• 2+ years in BDR/SDR or sales (B2B SaaS; AI/GenAI a plus). Strong track record sourcing pipeline; enterprise experience preferred.
• Comfortable learning technical concepts and translating GenAI into clear business value.
• Proactive, organized, iterative, creative, adaptable, and enjoy testing messaging and improving processes.
• Existing Fortune 500 network is a plus, not required. ABOUT STACKAI Stack AI is a no-code drag-and-drop tool to quickly design, test, and deploy AI workflows that leverage Large Language Models (LLMs), such as ChatGPT, to automate any business process. Our core value is to make it extremely easy to build arbitrarily complex AI pipelines using a visual interface that allows you to connect different data sources with different AI models. Our customers use Stack AI to build applications such as:
• Chatbots and Assistants: AI agents that interact with users, answer questions, and complete tasks, using your internal data and APIs.
• Document Processing: apps to answer questions, summarize, and extract insights from any document, no matter how long.
• Answer Questions on Databases: connect GPT-like models to databases (such as Notion, Airtable, or Postgres) and ask questions about them.
• Content Creation: generate tags, summaries, and transfer styles or formats between documents and data sources.