About the job
Join Enter.ai!
Our mission is to position Brazil as a global leader in artificial intelligence.
At Enter.ai, we merge human expertise and artificial intelligence to execute critical, high-volume tasks that still rely on manual processes on a large scale. Our platform enables major companies across Latin America to navigate intricate workflows, starting with legal operations and expanding across the enterprise. We leverage AI to create tailored legal defenses at scale, assisting businesses in lowering costs and enhancing their litigation success rates.
Our team consists of the finest talents from prestigious institutions in Brazil and around the globe, including Harvard, UPenn, Stanford, ITA, USP, and Unicamp. Companies like Meta, Itaú, Mercado Livre, Latam, Airbnb, Santander, iFood, and Nubank partner with Enter.ai to manage critical processes more efficiently. With over R$300M raised and a valuation of R$2B, we have the backing of major investment funds like Sequoia and Founders Fund who share our vision for the future.
Position Overview
As a Software Engineer at Enter.ai, you will play a pivotal role in constructing the foundation of our AI agent platform. This position requires making critical technical decisions, defining architecture, and tackling scalability challenges while processing large volumes of data in production systems. You will engage with problems involving Backend, Machine Learning, and LLMs, enjoying a high degree of autonomy and accountability for the quality and advancement of our systems.
Key Responsibilities
Define and enhance the architecture of the systems supporting the AI agent platform, ensuring high availability, performance, and reliability.
Lead decisions regarding scalability, ensuring the platform evolves with increasing demand and complexity.
Design and implement solutions for processing large volumes of data while ensuring integrity, security, and efficiency at scale.
Collaborate with AI teams to integrate machine learning models and LLMs, ensuring their effective application in production.
Raise the technical standard of the team through code reviews, establishing best practices, and mentoring fellow engineers.
