Senior AI Engineer

Company Description Novagates is an Intelligence Infrastructure company enabling the next generation of enterprises to transform how they operate, engage customers, and accelerate growth. Built over four years of global collaboration with more than 800 engineers in 13 countries and over 50 industry consultants, Novagates integrates intelligent automation, commerce infrastructure, immersive experiences, and enterprise intelligence into a unified platform. This comprehensive infrastructure allows organizations to harness advanced AI and data capabilities to drive innovation and efficiency. Team members join a globally distributed, highly technical environment focused on building scalable, future-ready systems for modern enterprises.

Role Description The Senior AI Engineer is a full-time, remote role responsible for designing, building, and deploying AI and machine learning solutions that power Novagates’ Intelligence Infrastructure. Day-to-day activities include developing and optimizing models, implementing data pipelines, integrating AI services into production systems, and collaborating with product, engineering, and data teams to deliver scalable solutions. The person in this role will analyze complex business requirements, translate them into technical architectures, and ensure reliability, performance, and security of AI components. They will mentor other engineers, contribute to best practices and coding standards, and participate in code reviews, technical design discussions, and continuous improvement initiatives.

Qualifications

• Candidates should possess strong skills in core AI/ML engineering, such as machine learning model development, deep learning frameworks (e.g., PyTorch, TensorFlow), and algorithm optimization.
• Candidates should possess advanced software engineering skills, including proficiency in programming languages (e.g., Python, Java, or Go), API development, and building scalable distributed systems.
• Candidates should possess data-related skills, such as experience with data pipelines, data processing frameworks (e.g., Spark or similar), and working with structured and unstructured datasets.
• Candidates should possess cloud and infrastructure skills, including hands-on experience with major cloud platforms (e.g., AWS, Azure, or GCP), containerization/orchestration (Docker, Kubernetes), and CI/CD practices.
• Candidates should possess strong analytical and collaboration skills, including problem-solving, technical communication, cross-functional teamwork, and the ability to document and present complex solutions clearly.
• Relevant qualifications that would be beneficial include prior experience with enterprise AI solutions, knowledge of MLOps practices, exposure to automation and commerce systems, and a track record of delivering production-grade AI services.
• A bachelor’s or master’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience, is preferred, along with experience in senior or lead engineering roles.