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Safari AI is building computer vision AI to automate operations for leading companies in entertainment, retail, QSR, and live venues. The company works with clients like Merlin/Legoland, 7-Eleven, Tanger Outlets, and professional sports teams.
You will be Safari AI's first GTM Engineering Lead, reporting directly to the Founder & CEO. This is a strategic, in-office role based in Miami working alongside the GTM team to build AI agents that automate growth marketing, sales, client success, and partnership workflows.
Key responsibilities include:
- Developing AI agents to scale outreach and accelerate deal velocity across growth, sales, and client success functions
- Building prospect research and account-scoring pipelines that identify high-fit venues and enrich them with operational signals
- Designing and maintaining data pipelines powering outbound sequences, lead nurturing, and customer onboarding
- Creating vertical-specific demo environments and ROI calculators that translate Safari AI's computer vision outputs into buyer-relevant metrics
- Operating the outbound infrastructure stack (sending platform, CRM, enrichment, reply-handling agents) and tuning performance based on live data
- Working cross-functionally with sales, growth, and client success leaders to ship experiments quickly and feed learnings into product roadmap
Required experience:
- Daily hands-on experience building, deploying, and using AI agents
- Ability to design, implement, and operate independently
- AWS or similar public cloud experience
- Proficiency wiring together modern GTM tools (HubSpot, SmartLead, Clay, Apollo, Zapier/n8n, Notion) and writing Python or TypeScript
- Production experience prompting and orchestrating LLM APIs (Claude, OpenAI) for agents, classification, and structured output
- SQL and data warehouse experience (PostgreSQL, BigQuery, Snowflake)
- Self-motivated problem-solver with strong analytical and business acumen
Nice-to-haves include early-stage startup experience, B2B marketing/sales exposure, and prior success building internal tools adopted by non-engineering teams.
