About Arca

Arca is a wealth management firm built from the ground up with AI. Most people get financial advice that's reactive: an annual check-in, a plan that's a document instead of a living thing, a relationship where you're one of three hundred clients your advisor is trying to remember. We think that's backwards. The kind of service that used to require a team of specialists behind you, the kind that makes you feel like the only person in the room, should be available to far more than the ultra-wealthy.

So we're building it. We're not SaaS — we are the wealth management business, rebuilding it from the inside with AI. Our platform is an Iron Man suit for advisors: it takes over the low-leverage work so they can focus on what actually requires a human, showing up with empathy, context, and judgment. Underneath, it keeps a living understanding of each client. It remembers the thing you mentioned once, six months ago. It notices when your life changes — a new job, a new kid, a market shift — and adjusts before you think to ask. You won't see the technology. You'll just notice your advisor seems to know you better than any financial professional ever has.

That's the product we're growing: client by client, on the strength of the experience itself. We started by acquiring firms managing over $1B in client assets, which gave us real advisors, real clients, and real financial outcomes to build against from day one. But acquisition was the starting line. The bet is that an advisor backed by this platform delivers something good enough that clients come to us on their own.

It's a $20T market, and we think it's ready to be rebuilt.

— Rron, CEO

The receipts

Stage: Series A, $64M raised

Backed by: General Catalyst, Index Ventures, Venrock

Board & Advisors: Former CEO of Vanguard, Former CFO of Schwab, Founder of Altruist, Morgan Housel (author of The Psychology of Money)

The team

We’re small on purpose and engineering heavy: about 80% of the team is technical. We’re based in NYC and hail from high growth startups like Stripe, Ramp, Rippling, Plaid, Doordash, & Glean.

We’re fully in-office in Flatiron, five days a week—lunch together, coffee breaks, basketball games, happy hours.

The role

As a Member of Technical Staff focused on Product, you’ll own entire product domains end to end. You'll work directly with our advisors, operators, and clients to understand what they need, then prototype, ship, and iterate fast. If you ship it, you own it

What you’ll build (and own)

Advisor and operator surfaces. The tools your colleagues use to serve clients, built so one advisor can deliver high-touch service to far more clients than they could before. This is how the firm scales without the experience degrading.

Consumer portals. Where clients interact with their advisor, see their full financial picture, and engage on their own terms. This is also our organic growth engine: the surface that turns a good experience into clients who come to us on their own.

The AI that powers all of it. From the tools and skills agents use, to how those agents are embedded in the product itself. This is the layer that makes the other three feel intelligent rather than just digital.

Example problems you’d work on

These aren’t hypothetical; we’re actively working on versions of all of these.

A research agent advisors actually trust. An advisor prepping for a client meeting needs to know how a pending divorce affects an estate plan, cross-referenced with tax law and the client's portfolio. The agent has to search proprietary data, integrations, and the web, then synthesize something the advisor can act on without second-guessing. "Close enough" isn't acceptable here. The hard part is building a system that knows what it doesn't know, and surfaces that uncertainty in a way that builds trust, under real constraints: compliance, auditability, and datasets where a stale answer is as harmful as a wrong one.

Generative UI that doesn't break the advisor's flow. Our agents view and update the advisor's frontend in real time: dynamic scenarios, interactive plan adjustments, visualizations that shift as the conversation does. The challenge is ensuring agents can reliably render and manipulate our pages without feeling unpredictable. An advisor mid-call can't be troubleshooting their UI.