Head of Information Technology (Remote)

Employment type Full-time employee Department — Work location Remote Compensation $200,000 – $300,000 annually

Vantage is an AI-native portfolio intelligence platform for institutional capital allocators: venture funds, private equity firms, fund-of-funds, LPs, and family offices. We pair software with an embedded bench of analysts and operators who work directly inside our customers’ portfolios, so firms get not software or services, but both. Every metric we surface is citation-grounded: traceable to its source document and page, a standard that legacy platforms and general-purpose AI tools cannot match.

Today it gets from that PDF to the LP letter by way of an analyst, a spreadsheet, and a chain of copy-paste that nobody can audit and everybody trusts anyway. We are pre-launch, with a private alpha cohort live today. We are launching this year, in a category that is fragmented at best and where nobody has yet built the AI-native version of it at scale.

As Chief Technology Officer you own the transition from an early AI product to a production platform: the architecture, the engineering practices, the model evaluation loops, and the operational controls that let us scale customer trust. You are the first engineering leader we will hire, and the decisions that set our cost structure, our security posture, and our shipping speed for the next three years are all still open, and all yours.

The platform is in production with customers today. The job extending it across many more firms, more documents, and more of the work our customers hand us, while the traceability holds and cost per customer falls. The judgment we care about is what to build in what order, and where to invest early in the things that compound, extraction accuracy, evaluation, and unit economics, so that growth is a matter of adding customers rather than adding effort.

Vantage sells software with an embedded bench alongside it, and that bench runs on what you build. Its leverage is set by the systems behind it, so designing that tooling is part of this job rather than an adjacent concern.

Priorities move as we learn, and you will make consequential calls quickly and with incomplete information: what to build now, what to defer, and which risks are worth carrying. You will work directly with our CEO on strategy and roadmap, our Chief Commercial Officer on security and enterprise readiness, our Head of Product on what gets built, and our COO on the unit economics of running the platform. You will also be in front of customers. Most AI products are graded on plausibility. Ingestion over unstructured, inconsistent source documents. Quarterly reporting packs, cap tables, K-1s, board decks, side letters, ILPA templates, and one-off Excel files that every firm formats differently and no firm formats consistently. Every displayed figure resolves to a specific document and page. This is load-bearing on the data model, and it holds or fails at runtime rather than in review.

Every figure is grounded in a source, and the engineering work is proving that holds as the system scales: evaluation suites, runtime checks, and monitoring against the live platform. Our customers are regulated, so we surface sourced facts and leave recommendations and valuation opinions to them.

Fleet operations across isolated customer environments. Contracted analysts work inside environments holding LP-confidential data, which is the right answer for this data and a standing engineering problem for everything else. Shipping a change, keeping behavior consistent, and getting real observability across all of those environments at once is the ongoing work.

Alongside the platform, analysts and operators work inside customer environments on parts of the delivery. What they do by hand is work we have not yet built tooling for, and closing that distance is how onboarding gets faster and how each new customer costs less to serve than the last. Unit economics at scale. What a customer pays is fixed by contract. What they use is not: every document ingested and every query run costs us more and earns us nothing. Decide what to build, what to defer, and what risk to carry, and be able to explain each of those calls to people who will live with the consequences.

Own software gross margin. Instrument cost per customer, report it monthly, and hold the line as the customer base grows.

Own product security: environment isolation, access control, and the technical evidence behind our SOC 2, which our Chief Commercial Officer runs as a program.

Own the technology behind the embedded bench: the agent systems, workflow tooling, and quality controls that determine how much an analyst can carry and how quickly a new customer comes online.

Partner with services leadership on delivery model design, so that what we commit to customers and what the platform can support stay in the same place.

Own infrastructure, operations, and third‑party platform dependencies.

Represent Vantage technically in customer conversations, escalations, and diligence.

Build AI-first internally, not only in the product. Set engineering practices and culture, including how much process is enough and where more of it would only slow us down.

You ship your org chart. Whatever structure you draw will show up in the product within two quarters, which is a liability at most companies and an advantage here, because there is nothing to unwind. The first architecture decision and the first org decision are the same decision, and both are open.

You have shipped without a finished spec, decided what to leave broken on purpose, and carried real risk knowingly. Personally built a document extraction pipeline over messy real‑world documents and taken it to production accuracy. Production, with customers who noticed when it was wrong.

You have taken work that ran on people and moved it onto software with people in the loop, and you can say what the throughput was before and after.

Shipped an LLM‑backed product where being wrong was a business‑ending event, whether financial, legal, medical, regulated, or otherwise unforgiving, and can describe the mechanisms that made wrongness detectable. You tell engineers who the customer is and what has to be true, then let them find the answer. Private‑markets fluency: fund accounting, ILPA reporting, cap tables, capital account mechanics.

Experience as the first or second engineering leader at a company that went on to scale.

Enterprise B2B experience where human operators work inside customer environments.

A PhD. A brand‑name logo. Compliance certifications matter to our customers, but they are not what we are hiring you for. You need a mature platform, a defined process, and a finished spec to be effective.

Your strength is running a delivery process rather than understanding the product and the people building it.

You want distance from customers. Product, design, commercial, client success, and operations are in place and experienced, and most of us have built and sold software before. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other characteristic protected by applicable federal, state, or local law.