Our client is a fast-growing, AI-powered marketing platform currently being utilized by leading SaaS (Software as a Service) companies. As a dynamic startup of 30 people, they are rapidly expanding their team. They are looking for a highly skilled and motivated Senior Backend Engineer to join their globally distributed team, with a focus on incorporating talent from Latin America. Their engineering team operates across the US and India, and you will play a crucial role in maintaining and scaling our robust infrastructure.
This role is ideal for an experienced engineer who excels in a fast-paced environment, can work autonomously, and is dedicated to delivering high-quality, scalable solutions. If you are a proactive problem-solver with a strong background in Java and cloud technologies, we encourage you to apply.
Responsibilities:
Design, develop, and deploy robust, high-performance backend services primarily using Java.
Write and maintain clean, efficient, and well-documented code across various systems, including significant work with Python.
Work extensively with AWS services, particularly those related to message queuing and serverless architecture, to build and scale our platform.
Implement and manage distributed data pipelines and communication using Kafka.
Collaborate with cross-functional teams to define, design, and ship new features.
Ensure the scalability, security, and reliability of our applications and infrastructure.
Mentor junior engineers and contribute to technical decision-making and architectural discussions.
Requirements
6+ years of total professional experience in software development.
Expert-level proficiency in Java and its ecosystem.
A minimum of 2 years of hands-on experience with Python within the last five years of professional work.
Significant experience with AWS cloud services, including hands-on experience with SQS (Simple Queue Service) and other fundamental services (e.g., EC2, Lambda).
Strong, demonstrable experience working with Kafka for building real-time data feeds or distributed applications.
Working knowledge of containerization technologies: Docker and Kubernetes.
Proficiency with both relational and non-relational databases, specifically MongoDB and MySQL.
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Nice to Have:
Experience working with Large Language Models (LLMs), including integration, fine-tuning, or deployment in a production environment.