Senior AI Platform Engineer

The University of California, Riverside is seeking a Senior AI Platform Engineer to design, develop, and implement a scalable Generative AI platform for its community. This role involves leading the development of AI-driven microservices, creating chatbots for user interaction, and providing technical guidance on AI best practices.

Responsibilities:

• Lead the development of AI-driven microservices for university-wide application integration
• Develop campus chatbots for interacting with faculty, staff, students, prospective students, and the campus community
• Provide expert technical guidance and mentorship to development teams on generative AI best practices
• Establish and maintain robust AI/ML Ops pipelines for efficient model deployment and management
• Serve as a technical subject matter expert, ensuring the platform's architecture and implementation meet the university's technical requirements for AI integration

Requirements:

• Bachelor's degree in related area and/or equivalent experience/training
• Master's degree in related area and/or equivalent experience/training
• 6 - 10 years of related experience
• Advanced knowledge of secure software development
• Highly advanced skills associated with software specification, design, modification, implementation and deployment of large-scale scope
• Excellent project leadership and management skills
• Demonstrated ability to understand functional needs and how systems can support those needs
• Demonstrated ability to develop conversion and system implementation plans
• Advanced experience with identification and use of code libraries and open-source forums
• Advanced experience with planning for deployment and creation of feedback mechanisms
• Demonstrated software repository skills
• Experience developing and executing complex test plans
• Demonstrated effective communication and interpersonal skills
• Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization
• Self-motivated and works independently and as part of a team
• Able to learn effectively and meet deadlines
• Demonstrated complex problem-solving skills
• Expertise in Large Language Models (LLMs) and related frameworks (e.g., LangChain, Transformers)
• Proficiency in prompt engineering techniques for optimizing LLM performance
• Strong understanding of agentic AI concepts and experience in building agentic AI applications (e.g., using Google Agent Builder)
• Experience in designing and implementing AI/ML Ops pipelines for model deployment, monitoring, and management
• Proficiency in building and deploying RESTful APIs and microservices for AI integration
• Strong understanding of cloud platforms (e.g., Google Cloud Platform, AWS, Azure), particularly Google Vertex AI
• Experience in developing and deploying chatbot applications
• Knowledge of data privacy and security principles related to AI and machine learning
• Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes)