How Applicants Are Reshaping Their Portfolios to Pass MadeThis's Screen
MadeThis, a three-person Y Combinator company from the Fall 2025 batch, is hiring for four roles: Head of Research, Founding Engineer Platform, Forward Deployed Engineer, and Founding Account Executive. The company's product is an AI co-founder platform that gives users a team of AI employees to build, market, and run businesses, handling website creation, payments, customer communication, marketing, and daily operations from a single platform. Over 20,000 businesses have launched on it in the last 100 days, generating $100,000s in revenue, with customers ranging from first-time founders to business owners doing $50M+ per year, Y Combinator's launch post reports.
The three founders each carry backgrounds that align with the roles they're hiring for. Jacob Wright founded and scaled an AI consumer app past one million users, then joined RunPod as a founding engineer and later managed its forward-deployed engineering and growth teams during the run to $100M in revenue, Y Combinator's company page for MadeThis shows. Cambree Bernkopf led product design for Remi's consumer products at 19 while in Y Combinator's Winter 2022 batch. Santiago Gomez Paz researched synthetic data at MIT, managed product at Turing, and founded zaymo.com (YC W24) before launching MadeThis.
The enterprise tier promises "AI employees trained on your best people" — a living digital twin built from a company's tools in week two, trained on the team's skills by week four, with only six total hours of client time across the engagement. The platform integrates with Slack, Microsoft Teams, Email, SMS, WhatsApp, Telegram, Signal, iMessage, Discord, Voice, and tools including Google Drive, Gmail, QuickBooks, HubSpot, Notion, Linear, Jira, GitHub, and Calendar.
The Signal: Technical Depth Meets Product Thinking
The table below shows the four open roles with their compensation bands as listed on Y Combinator's jobs board.
| Role | Location | Base Salary | Equity | Experience Required |
|---|---|---|---|---|
| Founding Engineer, Platform | San Francisco, CA | $250K–$350K | 1.00%–5.00% | 3+ years |
| Forward Deployed Engineer | SF / NYC / Salt Lake City | $250K–$350K | 0.10%–1.00% | 3+ years |
| Head of Research | San Francisco, CA | $250K–$500K | 5.00%–10.00% | 6+ years |
| Founding Account Executive | SF / NYC / Salt Lake City | $150K–$300K | 0.10%–1.00% | 3+ years |
The product itself reinforces the technical bar. MadeThis sells an "AI co-founder platform" that spins up a coordinated team of AI employees, handling marketing, sales, ops, support, legal incorporation, payments, and paid ads. The enterprise tier promises a "digital twin of your company" and AI employees trained on how top performers actually work, deployed in four weeks. Building and maintaining that stack demands fluency across LLM orchestration, retrieval-augmented generation, eval frameworks, and the integration surface where model output meets business logic.
The founders have lived both sides; they built Castari as "Vercel for AI agents" before pivoting to the broader MadeThis platform, and scaled RunPod's growth engineering while the product evolved.
Four Roles, Two Engines
MadeThis is hiring for four positions that map to two engines driving its traction: the core platform that spins up autonomous businesses in under ten minutes, and the enterprise motion that sells custom AI teammates to companies doing $10M+ in revenue. The three-person founding team — Wright, Bernkopf, and Gomez Paz — needs specialists who can own entire problem spaces from day one.
The Founding Engineer, Platform sits at the center of the product. This role owns the infrastructure that translates a natural-language business description into a live operation: website, legal incorporation, payments, marketing content, paid ads, social integration, and the "team of AI teammates" that manage it all. The 1–5% equity range signals a founding-team-adjacent seat.
The Forward Deployed Engineer operates where the platform meets the enterprise. MadeThis's enterprise page describes building "a digital twin of your company, then standing up AI teammates" for mid-market customers. This role deploys those digital twins into $10M+ revenue businesses, integrating with existing workflows, data sources, and compliance requirements. The multi-location listing reflects the need to sit with customers. The equity band is lower than the founding engineer's, but the base is identical.
The Head of Research carries the widest compensation span and the steepest experience bar. That range reflects the ambiguity of the mandate: advancing the agent architectures that let MadeThis "conceive an autonomous business in less than 30 seconds." The platform already handles code generation, payments, marketing, and operations. The next frontier is reliability at scale — making AI teammates that can run a $50M business without human babysitting. Anthropic's research shows Claude now handles roughly 20 autonomous actions before needing human input, up from 10 six months ago. MadeThis needs someone pushing that curve for business operations, not just code.
The Founding Account Executive owns the enterprise sales motion from zero to repeatable. The listing targets companies "doing $10m+ in revenue" wanting "custom AI teammates", a consultative, technical sale into operations and C-suites. With three locations and a $150K–$300K base plus 0.1–1% equity, this is a builder role: defining the sales process, closing the first flagship accounts, and feeding product requirements back to the platform team. The "founding" prefix isn't decorative; there is no sales team to join.
Together, these roles reveal a company that has proven demand — paying customers from solo founders to $50M enterprises — and now needs to harden the platform, scale the enterprise motion, and push the agent ceiling, all without the luxury of junior hires to absorb the grunt work.
The Market Is Splitting in Two
AI startups now scale from $1 million to $30 million in revenue five times faster than SaaS companies did, according to Deloitte's 2025 tech trends report. That velocity compresses the knowledge half-life in AI to months instead of years.
The hiring market is bifurcating. Enterprises still treat AI as an upskilling problem: Deloitte's State of AI in the Enterprise survey found 53% of leaders prioritizing "educating the broader workforce to raise overall AI fluency," while only 36% are assessing targeted hiring of specialized talent. Meanwhile, the startups actually putting agents into production (just 11% of organizations have them live, though 38% are piloting) are hiring for a different profile entirely. They need people who have already navigated the pilot-to-production gap, because 40% of agentic projects are projected to fail by 2027, not from technical limits but from automating broken processes instead of redesigning operations, Gartner found.
The layoff wave across 2025 reinforces the same signal. Deepwatch, Fiverr, xAI, Scale AI, Atlassian, Microsoft, Google, Paycom, Just Eat, Canva, Chegg, Indeed, Glassdoor, Klue, Intel, Autodesk, Workday, Salesforce, Stripe, Textio, and Pocket FM all cut headcount while explicitly citing AI-driven efficiency or strategic pivot to AI. Simultaneously, Salesforce and Stripe are hiring aggressively for AI product roles. The net effect: the market is shedding generalist execution capacity and buying specialized delivery capacity.
YC-backed firms have codified this into operating doctrine. Broadcom's CIO told Deloitte: "Without focusing on a specific business problem and the value you want to derive, it could be easy to invest in AI and receive no return." Western Digital's CIO added: "We'd rather fail fast on small pilots than miss the wave entirely." Walmart's approach, involving store associates in building its scheduling app and cutting scheduling time from 90 minutes to 30, exemplifies the "design with people, not just for them" principle that separates production-grade AI teams from demo-grade ones.
New role taxonomies confirm the structural shift. Deloitte lists AI operations managers, human-AI interaction specialists, and quality stewards as emerging titles, roles that didn't exist three years ago. Organizational charts are flattening as AI absorbs routine execution; some companies are merging technology and people-leadership functions so systems and workforce design evolve together. The most successful organizations, per Deloitte, "reimagine jobs to seamlessly combine human strengths and AI capabilities."
The "build, buy, or borrow" workforce framework Deloitte recommends for manufacturers applies equally to AI startups: build core delivery talent, buy specialized model-optimization expertise, borrow commodity labeling or eval labor. MadeThis is in build mode for its core product loop. Candidates who internalize that by shipping portfolio projects that solve a real user problem end-to-end, documenting the trade-offs, and articulating the product reasoning are the ones advancing. The rest are being filtered out by a market that no longer pays for potential. The next screening call is already underway.
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