Chief Technology Officer - YC Startup

CTO leading a YC backed startup through a transformation to a forward deployed engineering model.

You will own engineering end to end:

Architecture. Set the technical direction for the agentic platform and the data infrastructure underneath. Drive the hard problems: high-accuracy extraction at scale, evals, schema mapping, agentic orchestration, and the data plumbing into customer systems of record.
Forward-deployed engineering. Build out and lead the FDE function that runs every customer engagement. This is the muscle that delivers the outcomes our customers pay us for, and the reason we win against horizontal infrastructure.
Hiring. Recruit and scale the engineering team beyond the current 4 engineers. We have a strong inbound pipeline and clear conviction on who we want.
Customer-facing technical leadership. Work directly with CTOs, CISOs, and heads of engineering at top-tier investment firms, plus CFOs and operations leaders at portfolio companies, on integrations, security reviews, and SOC 2 commitments.
Product partnership. Partner with the product co-founder on roadmap, prioritization, and the build vs. buy calls that matter.
Founder-level ownership. Sit in every important conversation: sales, customer success, board, fundraising.

Former founder or CTO. You've built and run a venture-backed startup before, ideally one that scaled. You know what it takes to go from 4 engineers to 30, and what it takes to be the technical face of the company in front of customers and investors.
Deep experience building production AI / LLM systems. Ideally agentic systems with high accuracy bars, not just RAG.
Comfort operating at the intersection of unstructured input and structured output: document AI, OCR, table extraction, schema mapping, evals, and the harness that holds it all together.
Track record of delivering into demanding enterprise customers at high velocity.
Willing to be in the office 5 days a week in NYC.

Experience with forward-deployed engineering or solutions architecture motions (Palantir FDE, Scale FDE, Ramp Solutions, etc.).
Background scaling engineering teams from sub-10 to 30+.
Open source contributions to AI / LLM agent tooling.

We partner with the largest investment firms in the world and their portfolio companies to get their data ready for agents.
We're moving from a pure-product motion to a forward-deployed engineering model.
For example, we help a large software PE portco structure the data trapped in their contracts (pricing, renewals, change-of-control terms) into clean form for M&A data migrations. What used to take a services team months takes our agents days.
Every large enterprise is racing to put Claude, GPT, and other frontier models on top of their data. The bottleneck isn't the model anymore, it's the data underneath. No off-the-shelf product reads enterprise documents end-to-end with the accuracy regulated workflows demand. Tables span pages. Formats vary by counterparty. OCR is unreliable. Audit and compliance teams need cell-level provenance. This isn't a self-serve doc parser. Our forward-deployed engineers embed with each customer, configure agents to their specific data and workflows, and own the outcome end-to-end. The work is harder, the relationships are deeper, and the moat compounds with every workbook we deliver. Two segments today: Investment firms. PE and credit fund accounting teams, fund administrators, KPOs, and deal teams at investment banks. Use cases include capital account spreading, subscription doc and K-1 processing, loan tape ingestion, and deal-level diligence extraction. Portfolio companies. PE firms own hundreds of operating companies and are under intense pressure to deliver AI-led value creation across them. Use cases include M&A data migration, contract structuring, vendor invoice processing, AR / AP automation, and ERP cutovers.