About Replay

We are building the first-ever bank for enterprise data. There are over 35 million businesses in the US alone, many of which are sitting on an asset they don’t know they have. At Replay, we help businesses monetize their historical operating data by licensing it to the frontier AI and data labs for model training. Replay sits at the intersection of advancing the frontier of AI, while helping companies generate millions in growth capital without having to give up equity, take on debt, or lay off employees.

Why Join Replay Now

We have scaled from $0 to a multi-eight-figure run rate in a matter of months

We have raised from top-tier investors, including Floodgate, Afore, Ludlow, and Hustle Fund

We are small enough that you will carry outsized responsibility and grow as quickly as the company does

You will partner with and build for some of the fastest and most important companies in the world

You will help build a massive, category-defining business from the ground floor

The Role

We're hiring full-stack product engineers to own hard customer problems from the first product decision through reliable production systems. You will work across UX, frontend, backend, data, testing, observability, and iteration—not simply one layer of the stack.

We have opportunities across three connected product areas: acquiring internal enterprise work data from the systems where it lives, guiding companies through dissolution, and building the product layer around a de-identification pipeline that makes sensitive data safe and useful. You do not need prior experience in these domains. Each opening is tied to a real area of ownership, and we will be clear early in the process about which current opening appears most relevant to your experience.

What You'll Do

Own ambiguous customer or internal-team problems from discovery through measurable production outcomes

Build coherent vertical slices across frontend, backend, workflow state, data, testing, observability, security, and release

Make complicated processes clear without hiding exceptions, uncertainty, or recovery paths

Diagnose difficult production behavior and remove recurring root causes

Establish useful measurements and improve customer, team, quality, or reliability outcomes

Create reusable product and engineering capabilities that make later work faster and safer

Use AI deeply in development and where it improves the product, with explicit evaluation and verification

Work directly with Product, Design, customers, domain experts, and other engineers

Problems You Might Own

The common thread across our product is turning difficult, failure-prone work into software people can understand and trust. These areas share one Full-Stack Product Engineer title and hiring bar, but they represent distinct work and ownership. You do not need to choose one when applying. We will discuss the most relevant current opening early, and the placement-specific portion of the interview will reflect that work.

Bring fragmented enterprise data into one trustworthy system

Customers need to bring internal work data out of many SaaS tools, APIs, files, and export processes. Build the product that takes them from “our data lives over there” to a successful, verified transfer. You might design provider-specific export journeys, model long-running transfer state, make failures and recovery understandable, or build contracts, fixtures, and acceptance tests that keep every new source from becoming a one-off. This also means maintaining clear provenance and health across every handoff.

Help companies navigate dissolution from start to finish

Build the software that helps a company wind down its operations responsibly. The product spans onboarding, forms, documents, auctions, permissions, government obligations, operational closeout, and the exceptions that appear along the way. You might model durable workflow state, generate or parse documents, reconcile conflicting information, design a safe team intervention, or make a consequential next step clear to a customer. The challenge is keeping the whole journey understandable and recoverable when reality deviates from the expected path.