Pulppo is building Shopify for the real estate brokerages in Latin America. We provide them with performance analytics software, automatic online property listings, a valuation tool and a CRM. We will charge 20% of the 166 billions dollars in annual commissions they generate. From our integrated tool we automate non-value added activities, and give visibility and transparency to agents (CRM) and customers (buyer collaboration, seller dashboard). By integrating the entire process, we empower agents to deliver an improved customer journey and more efficient process.
We are looking for strong multidisciplinary people with experience in consulting from top firms, startups (either founders or early team members that had generic roles and did a bit of everything) that want to get their hands dirty, build stuff and grow fast with us.
Location: Buenos Aires, Argentina
About Pulppo:
Pulppo is at the forefront of transforming the PropTech landscape by improving the way users buy and sell properties. As the first tech-enabled real estate broker for Latin America, we are dedicated to making property transactions simple, transparent, and joyful. After raising nearly $5MM in seed funding and joining prestigious accelerators in LATAM, we are assembling a team of top talent to achieve our ambitious goals.
Key Responsibilities:
Qualifications:
About You:
Compensation:
Why Join Us:
• Be part of a company that is changing the real estate landscape in Latin America.
• Work with a team of passionate and talented individuals.
• Opportunity to grow and develop your career in a fast-paced, dynamic environment.
• Contribute to a mission that aims to make property transactions simple, transparent, and joyful.
Our infrastructure is based on a microservice architecture. Each of the microservices use modern web technologies such as typescript, react, next.js and tailwind for the frontend and typescript, express.js and node.js for the backend. Even some of our microservices run in python (mostly for data-driven tasks or ML models). For databases we prefer using mongoDB, but we are open to the idea of using postgresql or other relational databases if they better solve the problem. We are also developing some machine learning and computer vision applications using keras, tensorflow and opencv (even some tensorflow.js for frontend apps). On the infrastructure side of things, all our microservices are dockerized and running on kubernetes (some on lambda functions/serverless).
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