Software Engineer - Backend

About AI71: AI71 is an industry leader in artificial intelligence, delivering innovative solutions that empower developers, businesses and governments to solve complex challenges. AI71 builds secure, enterprise-ready applications powered by cutting-edge technology—tailored for knowledge workers and sector-specific needs. AI71 bridges the gap between advanced AI and real-world impact. Guided by a strong commitment to research and responsibility, we create transformative solutions that drive progress and empower communities. The Role: We are seeking a highly skilled Staff Backend Engineer to design, build, and maintain the core infrastructure for AI-powered applications. You will work closely with machine learning engineers, data scientists, and frontend developers to create scalable, secure, and efficient backend systems that enable cutting-edge AI capabilities. What You’ll Do: • Design, develop, and maintain backend systems and APIs for AI-driven applications. • Optimize database architectures and data pipelines for efficient AI model training and inference. • Implement secure authentication, authorization, and data protection mechanisms. • Collaborate with cross-functional teams to integrate AI models into production environments. • Ensure system scalability, reliability, and performance through robust infrastructure design. • Develop monitoring and logging tools for tracking system health and model performance. • Write clean, efficient, and well-documented code following best practices. What You’ll Bring: • Bachelor's or Master’s degree in Computer Science, Software Engineering, or a related field. • 8+ years of experience in backend development, with expertise in Python, NodeJS • Strong experience with RESTful APIs, GraphQL, or gRPC. • Proficiency in database design and management (SQL and NoSQL databases such as PostgreSQL, MySQL, MongoDB, or Redis). • Experience with cloud platforms such as AWS, GCP, or Azure. • Knowledge of containerization and orchestration tools (Docker, Kubernetes). • Experience with distributed computing and microservices architectures. • Strong problem-solving skills and ability to work in a fast-paced environment. Preferred Qualifications: • Knowledge of message queues (Kafka, RabbitMQ) and event-driven architectures. • Exposure to LLMs, vector databases, and AI inference optimization. • Understanding of DevOps practices, CI/CD pipelines, and infrastructure as code (Terraform, Ansible). • Familiarity with MLOps and AI model deployment pipelines is a plus. Why AI71: • Mission-Driven Work: Work on cutting-edge AI applications with a talented and passionate team, solving real-world challenges in critical sectors. • Unparalleled Opportunity: This is a chance to innovate and solve real-world challenges using AI at a company with unique access to world-leading models and resources. • Career Growth: We offer competitive compensation, benefits, and significant career growth opportunities as a foundational member of the team. • World-Class Environment: Enjoy a flexible working environment and the latest tools & technologies needed to do your best work. Show more Show less

Bachelor's or Master’s degree in Computer Science, Software Engineering, or a related field. 8+ years of experience in backend development, with expertise in Python, NodeJS. Strong experience with RESTful APIs, GraphQL, or gRPC. Proficiency in database design and management (SQL and NoSQL databases such as PostgreSQL, MySQL, MongoDB, or Redis). Experience with cloud platforms such as AWS, GCP, or Azure. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience with distributed computing and microservices architectures.

Design, develop, and maintain backend systems and APIs for AI-driven applications. Optimize database architectures and data pipelines for efficient AI model training and inference. Implement secure authentication, authorization, and data protection mechanisms. Collaborate with cross-functional teams to integrate AI models into production environments. Ensure system scalability, reliability, and performance through robust infrastructure design. Develop monitoring and logging tools for tracking system health and model performance. Write clean, efficient, and well-documented code following best practices.