Generative AI Engineer

Company Description Laxora Software helps startups and established businesses build scalable digital products through custom software development, web and mobile applications, AI solutions, SaaS platforms, and cloud technologies. The company focuses on turning ideas into secure, high-performance, production-ready software tailored to each client's needs. By combining modern technology stacks, agile development practices, and strong engineering expertise, Laxora delivers reliable and efficient solutions. Team members collaborate in a dynamic environment where innovation, technical excellence, and continuous improvement are highly valued.
Role Description As a Generative AI Engineer, you will design, build, and optimize generative AI models and systems for client-facing and internal products. You will work closely with product managers, designers, and developers to translate business requirements into robust AI solutions, including text, image, and other multimodal generation. Daily responsibilities include experimenting with model architectures, fine-tuning and evaluating models, integrating AI services into web and mobile applications, and monitoring performance and reliability in production environments. You will also contribute to MLOps practices, documentation, and best practices for responsible and secure AI use. This is a full-time, remote role, requiring effective collaboration across distributed teams and time zones.
Qualifications

• Strong foundation in computer science and software engineering, with proficiency in Python and experience building production-grade applications or services.
• Experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with generative models such as LLMs, diffusion models, or transformer-based architectures.
• Hands-on experience with AI/ML tooling and platforms (e.g., Hugging Face, OpenAI/Anthropic APIs, vector databases, ML pipelines) and deploying models to cloud environments (AWS, GCP, or Azure).
• Knowledge of MLOps practices, including model evaluation, monitoring, versioning, and CI/CD workflows for AI systems.
• Ability to collaborate with cross-functional teams, translate product and business needs into technical solutions, and communicate complex AI concepts clearly to non-technical stakeholders.
• Bachelor's or master's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
• Experience working with startups or fast-paced product teams, and familiarity with agile development methodologies.
• Understanding of responsible AI principles, data privacy, and security considerations in designing and deploying AI solutions.