Gen AI Architect

Responsibilities:

• Design and lead the implementation of AI-driven solutions aimed at optimizing operational processes and workflows.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical specifications.
• Utilize pre-trained large language models (LLMs) and other Generative AI techniques to develop personalized responses tailored to operators' needs.
• Architect and oversee the development of knowledge bases and databases to store and retrieve relevant information efficiently.
• Implement unsupervised techniques for data categorization and classification to enhance recommendation accuracy.
• Explore and integrate state-of-the-art AI technologies and methodologies to continuously improve system performance.
• Ensure scalability, reliability, and security of AI solutions deployed in production environments.
• Stay updated on emerging trends and advancements in AI, machine learning, and related fields to drive innovation within the organization.

Requirements:

• Bachelor's degree or higher in Computer Science, Engineering, or a related field. Advanced degree preferred.
• Proven experience in designing and developing AI-driven solutions, with a focus on Generative AI and Natural Language Processing (NLP).
• Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks (e.g., TensorFlow, PyTorch).
• Strong understanding of large language models (LLMs) and their applications in text generation and understanding.
• Experience with cloud platforms (e.g., AWS, Azure) and related services for deploying and managing AI solutions.
• Solid understanding of software engineering principles, including design patterns, data structures, and algorithms.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.
• Strong analytical and problem-solving abilities, with a keen attention to detail.
• Demonstrated ability to drive innovation and lead technical initiatives from concept to production.

Preferred Qualifications:

• Experience with prompt engineering techniques for fine-tuning large language models.
• Knowledge of advanced machine learning techniques such as reinforcement learning and transfer learning.
• Familiarity with DevOps practices and tools for continuous integration and deployment (CI/CD).
• Experience working in Agile or other iterative development methodologies.
• Publications or contributions to the AI and machine learning community (e.g., research papers, open-source projects)