Every year there is over $1.5 trillion worth of home buying activity in the residential real estate market alone, and within it there are countless opportunities to introduce efficiencies and economic value for home buyers & sellers.
At Orchard we're building software for life's biggest financial decision: buying and selling a home. Our products solve problems along the entire lifecycle of the home-buying transaction: from finding your perfect home to coordinating with multiple parties along the way so that the entire experience is seamless.
In order to accomplish this we need to build products across three pillars:
Build new products that help our customers find their dream home and make managing complex real estate transactions simpler than ever.Learn More
Build and manage an ecosystem of home-grown tools and third-party software that work seamlessly together to help our internal teams deliver an exceptional customer experience.Learn More
Own the technical infrastructure that allows us to ingest, process, and analyze the data that powers our internal and external products, including our ML models.Learn More
Our consumer facing products are built to help home buyers find their perfect home, seamlessly complete the financing and transaction process, and sell their current home for top dollar on the market. Many of the products we develop are true industry firsts, helping bring the real estate transaction into the 21st century.
As an engineer working on our consumer applications you will:
In order to deliver a seamless experience to our customers, we need to reduce the complexity of end-to-end real estate transactions ourselves. The workflows to complete these transactions often span multiple roles and even businesses.
We've built Atlas, an operational hub which centralizes processes across all of our users and teams. The data & services behind Atlas also power our consumer applications, including our customer dashboard, as well as other domain-specific tools.
As an engineer working on The Atlas Platform, you will:
Some of Orchard's highest-leverage problems are on our Platform team: we need to innovate on how multiple businesses operate in tandem. These problems give engineers business domain exposure, ownership and influence over how we shape the real estate industry for the future.
Data is one of the essential product pillars at Orchard. In order to deliver meaningful economic value to our customers, we are continuously improving our home valuation accuracy. This valuation accuracy not only gives customers higher confidence in the market value of their home - it also reduces the time otherwise mispriced homes can sit on on market and ensures buyers and sellers transact fairly. These models can only be as accurate as the quality and breadth of underlying data.
As an engineer working on data infrastructure you'll work with our data science team to productionize these models on top of infrastructure that processes data across a range of sources and geographies.
You'll build and automate highly scalable, self-healing data processing systems that serve as the backbone of Orchard's multiple businesses and product lines.
You will also dive deep into the meaning of the data itself, discover potential use cases, extend Orchard's data platform, and offer new data models to product teams who are eager to tap into new insights and unlock new data product capabilities. Past examples of novel data productization include kitchen & yard photo search filters built on neural network image classification.
Our technology stack consists of Python3 with type-hinting on the back-end and TypeScript & Angular on the front-end. We leverage RedShift for analytics pipelines, Python, SQL & Airflow to orchestrate ETL pipelines, and Static Site Compilation + Material Design components for low latency user experiences.
Our services are developed, built, tested and deployed via Docker containers on Kubernetes. We've architected our services to be stateless and elastically scalable under different load conditions.
Orchard's engineering culture is centered around product empathy and autonomous teams with high feature ownership. Engineers take ownership of feature development end to end. This means we partner with Product Managers and Designers to solve ambiguous business problems and have a high degree of collaborative input before writing code. We strive to keep common infrastructure and dependencies simple (or only as complex as necessary) to keep the coordination costs of infrastructure deployments low and support lean & nimble product engineering teams.
We've implemented PolicyGenius' Chartered Guild model. Rather than defining Guilds as specialist-affinity-groups, Chartered Guilds have problem-scoped mandates requiring them to spin-down after they've solved a concrete problem. Examples here include: increasing the green build rate of our CI pipelines & enhancing our security review process as part of system design.