Safari AI is a startup focused on automating operations in the physical economy using computer vision AI. The GTM Engineering Intern will work with the GTM team to automate workflows, design demos, and develop AI-powered tools to enhance client outreach and engagement.
Responsibilities:
- Build and iterate on AI-powered go-to-market tools that help Safari AI scale outreach and accelerate deals
- Develop solutions that are robust across customer contexts: varying industries, use cases, and stages of the sales funnel, ensuring a consistent and compelling prospect experience
- Work with a growing team of sales, marketing, and product engineers to ship GTM experiments quickly and feed learnings back into the product roadmap
- Design and maintain the systems, templates, and data pipelines that power outbound sequences, lead nurturing flows, and customer onboarding
- Build and maintain AI-driven prospect research and account-scoring pipelines that surface high-fit venues (stadiums, theme parks, retail, cruise, ski) and enrich them with operational signals (camera count, footprint, parent org, tech stack)
- Develop vertical-specific demo environments and ROI calculators that translate Safari AI's computer vision outputs (queue times, dwell, occupancy, conversion) into language and metrics each buyer persona cares about
- Operate the outbound infrastructure stack — sending platform, CRM, enrichment, and reply-handling agents — and continuously tune deliverability, persona logic, and conversation state machines based on live performance data
Requirements:
- Only students who can commit 6 months (2026/04-2027/01) will be screened
- Senior undergraduate or graduate school students in computer science or relevant field with exposure to classic and modern computer vision and machine learning techniques
- Excellent written and verbal communication skills
- Self-motivated, critical thinking and enthusiastic in solving real-world problems
- Experience with public cloud such as GCP, Azure or AWS
- Ability to design, implement, present, and operate independently without oversight
- Good business insight and exceptional analytical skills
- Comfortable wiring together modern GTM tooling (HubSpot, SmartLead/Instantly, Clay, Apollo, Zapier/n8n, Notion) and writing light Python or TypeScript to glue systems together
- Hands-on experience prompting and orchestrating LLM APIs (Anthropic, OpenAI) for production use cases — not just chat, but agents, classification, and structured output
- Working knowledge of SQL and at least one data warehouse or relational DB (PostgreSQL, BigQuery, Snowflake)
- Experiences in startup environment
- Exposure to B2B enterprise sales motions, especially with non-technical buyers in physical-venue industries (sports, hospitality, retail, attractions)
- Familiarity with computer vision concepts and the operational realities of CCTV/IP camera deployments
- Prior work building internal tools, dashboards, or AI agents that were actually adopted by a non-engineering team