About the job
Intercom is a pioneering AI Customer Service company dedicated to enhancing the customer experience for businesses worldwide.
Our flagship AI agent, Fin, represents the pinnacle of customer service AI technology. It empowers businesses to offer seamless, 24/7 customer service, significantly improving their customer engagement. When integrated with our Helpdesk, Fin evolves into the Intercom Customer Service Suite, providing AI-augmented support for complex inquiries that necessitate human intervention.
Since our establishment in 2011, we have earned the trust of nearly 30,000 businesses globally, setting the benchmark for unparalleled customer service. Our core values drive us to innovate, act with speed and intensity, and deliver exceptional value to our clients.
What is the opportunity?
Join our Research, Analytics & Data Science (RAD) team, where we transform insights into actionable strategies. We analyze customer, product, and business data, translating them into tools that integrate seamlessly into go-to-market (GTM) workflows.
The advent of AI has ushered in a new era of internal tools for our GTM teams. We are progressing from traditional dashboards to sophisticated workflows powered by large language models (LLMs) and AI agents that are capable of autonomously conducting account research, summarizing previous interactions, drafting tailored outreach, identifying renewal risks, and generating reports, thereby allowing Sales and Success teams to concentrate on high-impact conversations.
The RAD team collaborates closely with GTM Systems to identify challenges, devise solutions, and evaluate their impact from prototype through to production.
This role demands a high level of ownership from someone who thrives in uncertain environments, is passionate about solving intricate real-world challenges, and gains satisfaction from seeing their contributions lead to measurable business results.
What will I be doing?
- Design, evaluate, and deploy AI-powered internal tools for GTM applications, including account research and summaries, recommendations for next steps, renewal likelihood assessments, pipeline risk identification, and post-call follow-ups.
- Manage the entire lifecycle: Take ownership from problem identification and data modeling to the development of production-ready tools, including creating Python backends and React frontends.
- Rapid prototyping and deployment: Collaborate with users to build quickly, then iterate and enhance for maximum impact.
- Measure for success: Define success metrics based on actual usage and quantifiable business outcomes.

