CTO

Chief Technology Officer

• YC Startup

New York City · Full-time · In-person · Confidential search What we're building ProSights partners with the largest investment firms in the world and their portfolio companies to turn enterprise documents into AI-ready data infrastructure.

We started with high-accuracy extraction for investment workflows and are now moving deeper into forward-deployed data infrastructure: agents that ingest files from SharePoint, OneDrive, Box, Google Drive, email, and other systems, extract the right data, map it to schemas, preserve provenance, and push clean outputs into the customer's systems of record.

The bottleneck today is whether the enterprise can trust the data underneath it: inconsistent contracts, multi-page tables, unreliable OCR, changing amendments, and audit teams that need cell-level provenance.

Our engineers embed with customers, configure workflows around their actual data, and own the outcome end-to-end.

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 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.

Our unfair advantage 80% of the top 20 PE funds in the world are already customers. Deal teams are connecting us to operating partners who are deploying us into their portfolio companies, where our forward-deployed engineering team runs the rollouts. We get warm-introed by the GP.

About us

YC-backed (W24). $0 to $1.2M ARR in 11 months, with the latest SAFE at a $40M cap. Lean team of 8 in NYC: two founders, four engineers, one sales hire, and our current CTO.

The founder story is tied directly to the customer problem. Our CEO came from investment banking / private equity and lived the manual document, model, reconciliation, and audit-trail work from the buyer side. The engineering team turned that pain into production systems for the largest PE funds, not a demo wrapper.

Our current CTO built the technical foundation that got us here and is helping with the transition. He is moving toward a later-stage, lower-intensity role. We are hiring the successor for the next phase: the technical face of the company with customers, the person who turns messy enterprise deployments into repeatable architecture, and the leader who can raise the engineering bar without turning us into a process-heavy org.

The role You will own engineering from customer problem to production system:

• Technical leadership. Set technical direction for the agentic platform and the data infrastructure underneath: high-accuracy extraction, evals, schema mapping, agentic orchestration, and plumbing into customer systems of record.
• Customer-facing systems design. Sit with PE firms and portfolio companies, translate messy workflow requests into technical plans, and turn bespoke deployments into repeatable systems.
• Hands-on execution. In the first phase, expect 30-50% coding / deep technical work. Over time, this should become more architecture, review, customer translation, and team leadership.
• Forward-deployed engineering. Build and lead the function that runs customer engagements end-to-end. This is the muscle that delivers the outcomes customers pay us for.
• Hiring. Recruit and scale the engineering team beyond the current four engineers. The path could be four to six engineers or four to forty depending on customer pull and financing.
• Product partnership. Partner with the product co-founder on roadmap, prioritization, and build-vs-buy calls.
• Founder-level ownership. Sit in the important conversations across sales, customer success, technical diligence, hiring, and fundraising.

First 30 / 60 / 90 days

• First 30 days. Earn technical trust inside a strong engineering team, review the existing architecture, and lead technical design for a multi-system ingestion agent for a top PE customer portfolio rollout: SharePoint / OneDrive / email ingestion, schema mapping, provenance, evals, QA, and handoff into systems of record.
• Days 31-60. Convert the first customer-specific deployment into a reusable platform pattern: ingestion connectors, extraction and eval harnesses, schema/versioning rules, citation UX, and deployment playbooks that the forward-deployed team can repeat across PE firms and portfolio companies.
• Days 61-90. Own the customer-facing technical room with CTOs, CISOs, heads of engineering, CFOs, and operators; make the build-vs-configure calls; and decide which two to four engineers or forward-deployed engineers we should hire next.
• By day 90, the company should feel it has a technical cofounder-level owner: customers trust you, engineers learn from you, and Aaron / product are no longer the bottleneck on technical judgment.

What we're looking for

• Technical cofounder profile. You may be an ex-founder, CTO, founding engineer, or staff / principal engineer who wants the ownership level of a cofounder seat.
• Big-tech plus startup scar tissue. The ideal pattern is several years at a Meta / Google-caliber engineering environment plus meaningful startup or founding-engineer experience.
• Current hands-on ability. You are strong enough to code, debug, review architecture, and use tools like Codex / Claude Code thoughtfully. The team needs to feel it can learn from you technically.
• Customer-facing judgment. You can sit with demanding enterprise customers, separate stated asks from the real workflow, and translate ambiguity into technical execution.
• Enterprise data instincts. You understand why document AI fails in production: OCR noise, schema drift, table extraction, source citations, evals, permissions, and system-of-record handoff.
• Hiring and leadership. You can manage strong engineers without becoming a process-heavy enterprise VP Eng.
• NYC intensity. This is in-person in Chelsea. The right person wants a founder-level operating cadence, not a late-stage 9-to-5 role.

What this is not

• Not a pure IC research / ML role. You need to lead people and own customer outcomes.
• Not a late-stage VP Engineering job. There is no large org to administrate.
• Not a remote advisory role. We need someone in the room with the team and with customers.
• Not a generic enterprise data role. The edge is messy document-heavy workflows, provenance, evals, and deployment into real customer systems.

Bonus

• Forward-deployed engineering or solutions architecture experience: Palantir FDE, Scale FDE, Ramp Solutions, or similar.
• Private-markets, fintech, enterprise AI, document AI, OCR, or workflow-automation experience.
• Evidence of recruiting pull. People would follow you into the company.
• Open-source or visible work in AI / LLM agent tooling.
• Visa transfers. We can consider transfers for exceptional candidates already in, or seriously committed to, NYC.