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Proton.ai

AI-driven sales optimization via data analytics

Founding GTM Engineer

Sales OperationsConfirmed live in the last 24 hours
Full-timeCambridge, MA, USAIn-person

About the Job

Requirements

  • You have built revenue systems from scratch, rather than only maintaining someone else’s systems.
  • You are an expert in HubSpot architecture and administration.
  • You have hands-on experience with Clay, including the ability to describe Clay tables you have built.
  • You have a deep, active interest in AI, keep up with releases, experiment regularly, integrate AI into your workflows, and build with AI tools.
  • You have production experience with Claude or comparable models for automation, enrichment, dashboards, agentic workflows, or MCP servers.
  • You have strong data intuition and can communicate effectively with executives, distinguishing important information from noise and translating between them.
  • You are comfortable taking ownership, moving urgently, and shipping amid ambiguity.

Responsibilities

  • Build AI agents from scratch to autonomously run go-to-market workflows, including lead enrichment and scoring, outbound campaign generation, pipeline hygiene, signal monitoring, forecast updates, compensation queries, and deal desk triage.
  • Own the HubSpot stack end to end, including data models, automations, and reporting, and ship workflows in response to product releases.
  • Build outbound automation, enrichment pipelines, signal-driven plays, and lead scoring in Clay, delivering clean systems without over-engineering.
  • Own customer relationship management hygiene end to end, including deduplication, validation rules, field governance, and ownership integrity, so dashboards, forecasts, and outbound plays rely on trusted data.
  • Instrument the lead-to-opportunity-to-closed-won funnel and own pipeline health, forecasting hygiene, and segment-level performance.
  • Build new-business and net revenue retention forecast models for executive and board preparation, with documented and defensible assumptions.
  • Design territory, coverage, and governance, including accurate segmentation, clean ownership transitions, and documented operating rhythms.
  • Monitor developments in agentic AI, including model capabilities, tool-use patterns, multi-agent orchestration, Model Context Protocol, and evaluations, and bring relevant developments into production.
  • Build reusable agent infrastructure and documentation that enable the go-to-market team to operate and trust the systems.
  • Take projects from prototype through deployment, monitoring, and iteration.

About the Company

Proton.ai

AI-driven sales optimization via data analytics

Proton.ai provides AI-driven sales solutions for B2B teams. It collects and analyzes data from six sales channels to build a single, comprehensive view of each customer, enabling sales reps to run highly personalized and targeted outreach. The platform uses data analytics and machine learning to translate raw data into actionable insights and recommendations, which are delivered through a subscription-based platform. The company differentiates itself by integrating multi-channel data into one unified profile and by focusing on measurable outcomes, such as a 5-10% increase in total revenue and a 10% lift in average order value for mid-to-large enterprises. Proton.ai’s goal is to help businesses modernize their sales processes, improve customer engagement, and grow revenue by delivering data-driven, personalized selling at scale.

Company size
51-200
Company stage
Series A
Total funding
$30M
Headquarters
Cambridge, MA
Founded
2018

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