Scaling a SaaS platform powered by AI involves more than just deploying a large language model. For an LLM engineer, the process begins with a solid checklist — starting from selecting the right model architecture to optimising inference speed for production use. Key tasks often include fine-tuning the model on domain-specific data, setting up secure and efficient data pipelines, and integrating real-time feedback loops to monitor performance and user satisfaction.

Another crucial point on the LLM engineer's checklist is ensuring compliance with data privacy laws like GDPR while maintaining ethical AI standards. As SaaS platforms expand, engineers must also work on containerisation, cloud scaling (using services like AWS or GCP), and reducing latency for high-traffic usage. With so many moving parts, having the right engineering talent becomes a critical success factor for growth-stage SaaS startups.

If you're a business or startup looking to scale your SaaS product with cutting-edge AI, Magic Factory can connect you with top-tier LLM engineers in less than 7 days. From model deployment to ongoing optimisation, we help you build the right team to move fast and grow smart.

https://magicfactory.tech/hire-ai-developers/