Founding Software Engineer - AI, Data and Cloud Architecture

All In On Data β€” United States Β· Posted ~2 hours ago

Lead Full-time

Skills

Software architecture AWS Cloud engineering Data engineering Data infrastructure AI systems Retrieval pipelines Deployment System design AI Data pipelines Cloud infrastructure

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Summary ✨ AI‑Generated

A founding software engineering role for an early-stage venture where you will build the technology platform from the ground up. You will own cloud architecture, data infrastructure, deployment, and AI-native systems, transforming complex datasets into reliable, queryable information while choosing and evolving the technical stack.

Highlights

Exceptional end-to-end ownership as a founding engineer, with freedom to choose the technology stack and architecture. The role combines cloud infrastructure, data engineering, AI-native systems, retrieval pipelines, and automation while offering substantial autonomy and direct technical impact.

Description

The short version We are an early-stage real estate venture, and we are hiring the engineer who will build our technology from nothing. Not a team. Not a backlog handed down from a product org. You, a business problem, and the freedom to architect the answer. If you have rebuilt how you work β€” agents, evals, retrieval pipelines, AI-assisted refactors that would have taken a team a quarter β€” and you have been waiting for a role where that is the point rather than a side experiment, read on. What you'll do You are the founding engineer. That means you own the whole surface: Architect and build our cloud platform on AWS β€” the data layer, the services, the pipelines, the deployment story. You choose the stack. You live with the consequences.Design and operate the data infrastructure that turns messy real estate data β€” listings, comps, title records, market feeds, financials, documents β€” into something queryable, trustworthy, and fast.Build AI-native systems, not AI features bolted onto a CRUD app. Retrieval over unstructured property and transaction documents. Agentic workflows that do real work end-to-end. Evaluation harnesses so we know when a change made things better or worse.Use AI tooling as a primary engineering surface. We expect your output to reflect the leverage modern tooling gives a strong engineer. We will ask you to show us.Make the calls. Build vs. buy, managed vs. self-hosted, where to take on debt and where not to. There is no architecture review board. There is you and a business that needs to move.Set the standard the rest of the engineering org will inherit β€” testing, CI/CD, observability, security, documentation. What we are looking for: Core requirements: Legally authorized to work in the United States. This role is not eligible for visa sponsorship.10+ years, or equivalent demonstrated depth, building and shipping production software. Real systems, real users, real operational responsibility.Deep AWS. Not "I've used Lambda." You have designed multi-service architectures, made cost and scaling tradeoffs deliberately, and debugged them under pressure. IAM, VPC, RDS, S3, ECS/EKS, and the serverless stack should all be familiar territory.Serious database expertise. Relational and non-relational. You can model a schema properly, read a query plan, find the index that's missing, and explain why the ORM is lying to you.Data engineering depth. Ingestion, transformation, orchestration, warehousing, data quality. You have built pipelines that other people's decisions depended on.Real AI/ML engineering experience. RAG and retrieval architecture, vector stores, agent orchestration, prompt and context engineering, model evaluation. You know the difference between a demo and a system that holds up under load and scrutiny.You are an engineer. You bring systems thinking, rigor, and judgment about tradeoffs β€” not just fluency with tools. Just as important: You operate without supervision. Nobody will assign you tickets. You will scope the work, prioritize it, and report back on what matters.Self-motivated and serious. This is a role for someone who takes their craft seriously and wants ownership, not oversight.You communicate clearly with non-engineers. A meaningful share of your time will be spent with people who care about deals and returns, not distributed systems. Strongly preferred: An Anthropic credential β€” Claude Code, Claude Developer, or equivalent β€” or the ability to demonstrate comparable depth in practice.Real estate domain knowledge β€” brokerage, investment, property management, proptech, title, lending, or CRE data. Not required, but it will shorten your ramp considerably.Early-stage or founding-engineer experience. About the interview: We will ask you to walk us through a system you built where AI tooling was central β€” in genuine technical detail. What you delegated to the model and what you didn't. Where it failed you and how you caught it. How you evaluated correctness. What the architecture looked like and why. Come prepared to go deep. Surface-level answers here are the fastest way out of the process. Structure & Logistics Hybrid, in Beverly Hills. We want to build this in the same room for a meaningful part of the week, so we are looking for candidates in the greater Los Angeles area. If you need an accommodation to this expectation, tell us and we will engage with the request in good faith.You will be working directly with the founders. Short feedback loops, fast decisions, no politics. To apply Send your resume to hiring@scout-re.com along with a short note on the most technically interesting thing you have built with AI tooling β€” what it did, how it was architected, and what you learned when it broke. people who care about deals and returns, not distributed systems.