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How to Actually Get Hired
Who reads applications, which channel gets a reply, and what they screen for.
What gets their attention
The founding team is already ~12 people and productively deployed with design partners. The company page is explicit: "Production AI experience. Enterprise standards. Startup speed." The team composition as listed on the company page reveals the functional shape of the hiring plan. Security and operations are already staffed at the founding level (Mario Duarte on security, Marco Castillo on operations, multiple engineers, product members). The gaps that will open next are the commercial and AI-product layers: enterprise sales, customer success for complex IT environments, and AI engineers who can extend the agent capabilities.
Why applying the normal way doesn't work
With only <50 employees, WHIRL AI doesn't have dedicated recruiters. Founders review applications between running the company. The challenge isn't competition — it's visibility. Direct outreach wins.
Who to contact at WHIRL AI
Founding team
Sunny's career is one of the cleanest examples of founder-market fit in enterprise AI right now. He holds a BS and MBA from the University of San Francisco, and completed Executive Education in Leadership and Technology at Stanford. His career began in consulting at Andersen Consulting and Deloitte, where he built the foundational understanding of enterprise system complexity that defines his entire professional perspective. He then moved through a sequence of corporate IT leadership roles that trace the arc of enterprise technology itself: VMware, where he built operational infrastructure during one of the most consequential periods in enterprise virtualisation; JDSU, a telecom equipment manufacturer with highly complex operational systems; and then NVIDIA from 2008 to 2020, where he joined when the company had fewer than 2,000 employees and left when it had over 15,000, building and scaling the IT and operations infrastructure that supported the company's transformation from gaming GPU maker into the world's most strategically important AI hardware company. That twelve-year tenure at NVIDIA is the central credential. Scaling IT infrastructure from 2,000 to 15,000 employees across the period when NVIDIA was becoming NVIDIA is not a typical enterprise IT experience. He then joined Snowflake in January 2020 as CIO and Chief Digital Officer, where he became a public advocate for "Snowflake on Snowflake", the philosophy of using Snowflake's own products internally to demonstrate their value to customers. ICONIQ partner Matt Jacobson watched him operate in this role firsthand, which is why ICONIQ's first seed investment is in Whirl. His public writing on LinkedIn consistently returns to the same theme: "Every CIO I know wants to use AI to make IT more responsive and transformational. But it keeps stalling." He launched Whirl specifically because he believes no one else was solving the right underlying problem.
Marco's background is in enterprise GTM strategy at DocuSign, where he held the role of VP of GTM Strategy and scaled the operation significantly during a period of rapid growth. The company page describes him as a "GTM leader who scaled DocuSign 8X and lived the same problem from the business side," which is a precise framing: DocuSign's agreement management platform operates inside enterprise systems and faces the same context and integration complexity that Whirl is solving, but from the customer side rather than the IT side. Marco's decade-plus at DocuSign, across strategy and operations, gives Whirl's commercial function the enterprise GTM muscle that complements Sunny's product and market insight. He studied at the Tuck School of Business at Dartmouth.
What to show them
Whirl's core technical challenge is maintaining a continuously updated, structured knowledge graph of enterprise system context across applications, integrations, and configurations. The AI agents that operate on top of that context need to be able to reason across it reliably, handle ambiguity when documentation is incomplete, and surface changes when environments evolve. Building that layer at the reliability standard enterprise IT demands is a hard engineering problem. Core skills: Python, knowledge graph architecture or graph databases (Neo4j or similar), LLM orchestration for enterprise tool integration, ERP/CRM system integration (Salesforce, SAP, ServiceNow), structured metadata extraction, enterprise security standards, agentic AI systems. Proof of work: Map the technical architecture for a system that could continuously ingest metadata from Salesforce and ServiceNow simultaneously, identify the integration dependencies between them, and surface a change log when a new workflow is created in either system. Even a one-page design doc shows you understand the system intelligence problem Whirl is solving before the conversation starts.
A cold email that works at WHIRL AI
What WHIRL AI screens for
What they look for: The founding team is already ~12 people and productively deployed with design partners. The company page is explicit: "Production AI experience. Enterprise standards. Startup speed." The team composition as listed on the company page reveals the functional shape of the hiring plan. Security and operations are already staffed at the founding level (Mario Duarte on security, Marco Castillo on operations, multiple engineers, product members). The gaps that will open next are the commercial and AI-product layers: enterprise sales, customer success for complex IT environments, and AI engineers who can extend the agent capabilities.
Tailor your CV to the specific WHIRL AI role rather than sending a general one. Applications that mirror the language of the job description clear automated filters at a materially higher rate.
Mistakes that kill applications
Don't send the same CV you sent everywhere else. At <50 people it's obvious, and it's the fastest rejection there is.
Lead with their problem, not your ambition. WHIRL AI is focused on ICONIQ is primarily a growth-stage fund — show you understand that.
Most AI applications get ghosted. A day-five follow-up can double your response rate.
Frequently asked questions
How do I apply to WHIRL AI?
Through the roles on our WHIRL AI jobs page, or directly to a founder or department head if you can reach them. At <50 people, direct outreach outperforms the form.
Does WHIRL AI respond to cold emails?
We haven't verified response rates at WHIRL AI yet.
Who is the hiring manager at WHIRL AI?
At this size, hiring is usually run by a founder or department head.
How competitive is it to get hired at WHIRL AI?
Roles at <50-person AI companies typically draw 50-100 applicants in the first two weeks. Applying inside 72 hours of a posting going live is the single biggest lever you control.
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