RAG and LLM Systems Engineer, Enterprise AI

About the Role

As a RAG and LLM Systems Engineer, Enterprise AI at Qfyre TechLabs, you will be responsible for designing, developing, and deploying large-scale AI and machine learning systems that integrate with various enterprise applications. Your primary focus will be on building and maintaining robust RAG (Reactive Analytics Gateway) and LLM (Large Language Model) systems that can handle high volumes of data and provide real-time insights to business stakeholders.

You will work closely with cross-functional teams, including software development, data engineering, and product management, to ensure seamless integration and deployment of AI-powered solutions. Your expertise in full-stack development, document ingestion, and embedding pipelines will be crucial in building scalable and efficient systems.

Key Responsibilities

• Design and develop large-scale AI and machine learning systems that integrate with various enterprise applications.
• Build and maintain robust RAG and LLM systems that can handle high volumes of data and provide real-time insights to business stakeholders.
• Collaborate with cross-functional teams to ensure seamless integration and deployment of AI-powered solutions.
• Develop and implement document ingestion pipelines to feed large language models.
• Design and implement evaluation frameworks to measure the performance of LLM systems.
• Monitor and optimize production systems to ensure high availability and performance.
• Stay up-to-date with the latest advancements in AI and machine learning and apply them to improve existing systems.

Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, AI, or related fields.
• Strong understanding of machine learning concepts, including supervised and unsupervised learning.
• Experience with full-stack development, including front-end and back-end technologies.
• Proficiency in programming languages such as Python, Java, or C++.
• Knowledge of document ingestion pipelines and large language models.
• Experience with evaluation frameworks and metrics for measuring LLM performance.
• Strong problem-solving skills and ability to work in a fast-paced environment.

What You'll Learn

As a RAG and LLM Systems Engineer, Enterprise AI at Qfyre TechLabs, you will have the opportunity to learn from experienced professionals and work on cutting-edge AI and machine learning projects. You will gain hands-on experience with large-scale system design, development, and deployment, as well as stay up-to-date with the latest advancements in AI and machine learning.

You will also have the chance to collaborate with cross-functional teams and develop your communication and project management skills. This role offers a unique opportunity to grow your career in AI and machine learning and make a meaningful impact on the business.

Resume Tip

When applying for this role, make sure to highlight your experience with machine learning concepts, full-stack development, and document ingestion pipelines. Emphasize your ability to work in a fast-paced environment and your strong problem-solving skills. Also, include any relevant projects or contributions to open-source repositories that demonstrate your expertise in AI and machine learning.