HomeVision

Mandatory Location: Buenos Aires or Rosario (Argentina)

Stack: Go (preferred), React, TypeScript, AWS

About HomeVision

HomeVision is building the next generation of AI-powered software for the $13 trillion mortgage industry. Our platform, MIRA (Machine Intelligence Review Assistant), automates labor-intensive document processing and underwriting, helping lenders close loans faster and with less friction - ultimately saving borrowers time, money, and stress. We have already transformed appraisal operations for the country's top lenders, cutting review times by over 75%. Now, we are aggressively expanding MIRA to cover the entire loan file - automating income, assets, and credit analysis - to create a holistic underwriting utility for the industry.

At HomeVision, we like working with hungry, smart, curious and kind people who enjoy hard problems and real responsibility. Engineers here own meaningful projects end to end, from design to deployment, and collaborate closely with product, design and our go-to-market teams. We value low ego, high ownership, clear communication, and respect for each other’s time. We always try to “do the loving thing” in how we work together and with our customers and partners.

About the Role

We are looking for a full-stack Software Engineer to join our core product team in Argentina. You will work directly with our founders, designers, and ML engineers to build the interfaces and infrastructure that power MIRA. This is not a "maintain the legacy code" role; you will be architecting new features that allow complex AI decisions to be understood and acted upon by real humans.

What You Will Do

• Ship Product End-to-End: You will own features from database schema to UI components. You'll build the interfaces that underwriters use to interact with our AI, making complex data intuitive and actionable.

• Architect for Scale: Design and implement robust solutions that handle complex loan file data, ensuring high availability and low latency as we scale to millions of documents.

• Bridge the AI Gap: Work closely with our ML team to integrate AI services into our core SaaS platform, ensuring seamless handoffs between our decisioning models and the user application.

• Elevate Engineering Culture: Drive continuous improvement by championing effective development practices and the adoption of new AI-powered tools to increase our velocity and improve the stability of our production environment.

What You Will Bring

Technical expertise

• Production Experience: 4+ years of software engineering experience (not applicable for ECs), with a track record of shipping high-quality code in a production environment.

• Backend Fluency: Strong experience with Go (preferred), Java, C++, or similar strongly typed languages. You understand concurrency, data modeling, and distributed systems.

• Frontend Competence: Proficiency with React, TypeScript, or similar modern JS frameworks. You don't need to be a designer, but you should be comfortable building and debugging complex UIs.

• Cloud Native Mindset: Experience building on AWS (Lambda, SQS, S3) and familiarity with containerization (Docker).

• Ownership: You have experience (or a strong desire) to lead projects. You don't just write code; you take responsibility for the outcome.

Bonus Points

• Experience with Python in a data/ML context (pandas, numpy, etc.).

• Background in Fintech, Mortgage Tech, or complex workflow automation.

• Experience with Infrastructure-as-Code (Terraform/Pulumi) or DevOps practices.

Soft Skills

• Strong empathy for users and a habit of thinking through edge cases.

• A product mindset, focusing on how features solve real customer problems.

• Clear communication and a collaborative approach to working with teammates.

• Willingness to ask questions, share progress early and learn from feedback.

• Sense of ownership over the quality and reliability of your work.

Selection's Process

1. Silver Screen Interview

2. Client Take-home challenge

3. Client Resume & Take-home review

4. Client Technical Interview

5. Client System Design Interview