AI Architect

As an AI Engineer/Architect, you will play a crucial role in designing, developing, and deploying SaaS products that leverage advanced Large Language Models (LLMs) like Meta, Azure OpenAI, Claude, and Mistral. Your primary focus will be on leading the development process from conceptualization to deployment, ensuring seamless integration of AI models with business requirements and user needs. Your ability to build secure, scalable, and efficient SaaS products while complying with security and governance standards will be essential. Collaboration with product management and other stakeholders will be a key aspect of your role to align AI-driven SaaS solutions with business strategies and customer expectations. Additionally, you will be responsible for fine-tuning AI models to tailor them for specific use cases and optimize performance using techniques like quantization and model tuning. Your expertise in architecting AI deployment strategies using cloud-agnostic platforms such as AWS, Azure, and Google Cloud will be crucial for ensuring cost optimization while maintaining performance and scalability. Implementing retrieval-augmented generation (RAG) techniques to build AI models that provide contextually accurate outputs will also be part of your responsibilities. Furthermore, you will be integrating APIs and third-party services into the SaaS ecosystem to ensure a robust and flexible product architecture. Monitoring the performance of the products post-launch, iterating on improvements, and enhancing user experience and scalability will be essential for the success of the AI-driven SaaS solutions you develop. To be successful in this role, you should have a Bachelor's degree or equivalent in Information Systems, Computer Science, or related fields, along with at least 6 years of experience in product development, with a minimum of 2 years focused on AI-based SaaS products. Your hands-on experience with LLMs and SaaS platforms, as well as your proficiency in AI engineering, machine learning algorithms, deep learning architectures, and integrating models into SaaS environments, will be highly valued. Strong communication and collaboration skills are essential for working cross-functionally and ensuring the success of SaaS products. Keeping up to date with AI advancements, SaaS development trends, and cloud technology will allow you to apply innovative solutions effectively in product development.,