SafetyKit

Owns full sales cycle for enterprise customers fighting fraud on platforms, from discovery to close and expansion. Requires 3-7+ years selling SaaS/infrastructure to technical stakeholders with track record in complex, high-ACV deals.

Generates qualified sales opportunities through personalized outbound outreach, stakeholder research, and PQL qualification for enterprise SaaS customers. Requires 1-3+ years BDR/SDR experience, strong research skills, and in-office work in San Francisco.

Owns all marketing functions including field marketing, brand storytelling, product positioning, and demand generation campaigns for a Trust & Safety AI startup. Requires 4+ years experience across marketing disciplines, strong storytelling, and startup scrappiness; fully onsite in San Francisco.

Owns full sales lifecycle for enterprise deals ($100k-$1M ACV), from prospecting to closing, with cross-sell/upsell focus. Requires 3+ years sales experience hitting $2M+ revenue targets; onsite in San Francisco.

Designs beautiful, precise B2B SaaS products with AI agents, collaborates directly with engineers and customers to shape user experiences, and establishes brand identity. Requires exceptional taste, product intuition, curiosity, and fast execution.

Backend Engineer building scalable AI-agent infrastructure on AWS Serverless (Lambda, Step Functions, Aurora). Design high-performance systems, create monitoring/alerting, mentor team, and use codegen models to accelerate development while collaborating with AI/product teams.

Designs scalable AWS serverless infrastructure for AI agents in enterprise B2B SaaS, enabling rapid development by engineers and models. Leads technical decisions, mentors team, and drives best practices using TypeScript and CDK.

Develops novel AI agent applications using language models, manages model alpha program with OpenAI, architects risk AI workflows, and conducts experiments to evaluate model capabilities for B2B SaaS products.

Builds user interfaces and tools in React/TypeScript for customers to monitor and tune AI agent actions on enterprise platform data. Works directly with users, maintains frontend best practices, and leverages codegen for rapid development.