Founding Operator

Coastal Wave Recruiting•San Francisco, CA

21h

About The Position

Our client, a fast-growing AI startup transforming the $1.5T insurance brokerage industry, is hiring a Founding Operator to work hand-in-hand with leadership on the hardest, most ambiguous problems in the business. You'll put structure to chaos, ship outcomes in days not quarters, and own whatever matters most.

Requirements

1–4 years at MBB (McKinsey strongly preferred — SBA, tenured analyst, or early associate) or an elite boutique / bulge-bracket investment bank (M&A or ECM seat; Evercore, Jefferies, etc.)
Bachelor's degree from a top-tier university (e.g., CMU, Ivey, or comparable program)
Partner-level financial modeling, pricing analysis, and board-quality deliverables
Strong executive presence — able to hold your own with senior leadership, customers, and investors
Analytical rigor and a high quality bar across modeling, written work, and verbal communication
AI-native by default — a daily user of frontier models (GPT, Claude) who has already restructured personal workflows around them and can speak fluently to model capabilities
High-agency IC who imposes structure on ambiguity and ships without direction

Nice To Haves

Prior internship or stint at a high-growth startup or tech company (e.g., AI lab–acquired startup)
Exposure to technology, AI, FIG, or PE verticals in consulting/banking
Has built AI agents, internal tools, or side projects independently
Genuinely committed to startups/tech — ideally aspires to be a founder

Responsibilities

Own unstructured, high-stakes strategic problems — pricing, commercial strategy, board materials, and executive narratives
Run deep-dive analyses on account health, retention, expansion, and pipeline to inform GTM and customer strategy
Support enterprise deployments and onboarding alongside customer success for the largest brokerages
Build and operationalize GTM workflows, outbound automations, renewal motions, and internal reporting infrastructure
Build internal AI workflows, agents, and prompts that compress weeks of work into hours using frontier models