.Hi there!
We are South and our client is looking for a Principal Engineer!Note to Applicants:Eligibility: This position is open to candidates residing in Latin America.Application Language: Please submit your CV in English.
Applications submitted in other languages will not be considered.Professional Presentation: We encourage you to showcase your professional experience by including a Loom video in the application form.
While this is optional, candidates who provide a video presentation will be given priority.If this opportunity sounds good to you, send us your resume!About Company:Over the past four years, the founders of Company have collaborated with CXOs from the largest eCommerce companies globally, gaining unique insights that have shaped our vision for the future of commerce.
We believe the future will be defined at the intersection of personalization, aggregation, and social commerce.
Company is built on this thesis, and we're looking for a founding engineer to help bring this vision to life.With a combined 20 years of experience in founding venture-backed startups, consulting with Fortune 500 companies, and advising eCommerce giants, our founders are backed by prominent Silicon Valley investors.
We are now looking for a Principal Engineer who will play a pivotal role in shaping the product and technology for years to come.Responsibilities:System Architecture & DesignDistributed Systems: Design and build scalable, modern distributed systems (e.G., microservices, serverless architecture).Monolith to Microservices: Lead the process of breaking down monolithic systems into modular components.Data Storage: Design and manage high-read/write databases using relational (PostgreSQL) and NoSQL (MongoDB, DynamoDB) databases, along with caching solutions (e.G., Redis).API & System IntegrationAPI Development: Develop efficient, scalable APIs (RESTful or GraphQL) for serving recommendations and search results.Event-Driven Systems: Build message queues (e.G., RabbitMQ, Kafka) for service decoupling and design systems for asynchronous tasks.Search & Recommendation EnginesSearch Systems: Implement and optimize search systems using tools like Elasticsearch, creating indexes for quick lookups.Recommendation Engine: Build and optimize large-scale e-commerce recommendation algorithms, including product recommendations, user feed recommendations, and video/story recommendations.Machine Learning Integration: Design pipelines to integrate ML models, including inference, serving recommendations, and automating AI/ML workflows from development to production.Performance & ScalabilityScalability: Ensure high availability and performance of the platform to support millions of users and personalized recommendations.Monitoring: Implement logging, monitoring, and alerting systems (e.G., Prometheus, Datadog) for observability