Fellow AI Architect, Generative AI

About the Role

Key Responsibilities

• Define and drive the generative AI architecture strategy, ensuring UKG remains at the leading edge of AI innovation.
• Develop and communicate a cohesive architectural vision that aligns with business goals, enabling seamless integration of GenAI capabilities across products.
• Serve as the primary technical visionary for generative AI, providing hands-on guidance in advanced methods such as transformer models, diffusion models, and GANs.
• Work closely with executive leadership, product management, data science, and engineering teams to establish and prioritize GenAI initiatives.
• Conduct hands-on, advanced research in generative AI, staying current with emerging technologies, industry trends, and best practices.
• Lead the exploration and implementation of state-of-the-art GenAI techniques to enhance product value and maintain a competitive edge.
• Mentor and influence senior engineering leaders, fostering a culture of AI excellence, thought leadership, and continuous innovation.
• Represent UKG in the AI community through publications, speaking engagements, and industry forums.
• Oversee the deployment of large-scale AI models, ensuring they are optimized for performance, cost, and resource efficiency in production environments.
• Define and enforce development methodologies, CI/CD standards, and architectural guidelines for AI solutions.
• Maintain documentation of architectural decisions and technical roadmaps to ensure a sustainable foundation for future AI capabilities.

Requirements

• PhD in Computer Science, AI, Machine Learning, or a related field, or equivalent industry experience.
• 12+ years in software development and AI, with at least 5 years of hands-on experience in generative AI, NLP, or related fields.
• Proven expertise in architecting and deploying large-scale AI/ML systems in production environments.
• Expert-level skills in programming languages such as Python and Java, and AI frameworks like TensorFlow and PyTorch.
• Strong understanding of cloud platforms (AWS, Google Cloud, Azure) and MLOps practices for large-scale model training and deployment.
• In-depth knowledge of generative AI methodologies, including transformer models, diffusion models, GANs, and large language models.
• Familiarity with NLP and machine learning algorithms such as linear and logistic regression, decision trees, and clustering methods.
• Recognized thought leader in AI with publications in top-tier AI conferences/journals and a strong network within the AI research community.
• Exceptional problem-solving skills and ability to influence and implement long-term AI-driven strategic initiatives.

Nice to Have

• Experience working in high-compliance environments or with privacy-preserving AI techniques.
• Strong familiarity with trends in responsible AI, model interpretability, and ethical AI practices.
• Proven record of optimizing AI models for cost-efficiency through model compression, distillation, and efficient deployment strategies.
• Strong experience with cloud-native architectures, containerization (e.g., Kubernetes), and CI/CD pipeline automation (e.g., Terraform, GitHub Actions).

Qualifications

• Educational background with a PhD or equivalent industry experience in relevant fields.
• Extensive experience in AI and software development, particularly in generative AI and large-scale deployment.

Benefits & Perks

• Competitive salary range of $202,300 to $290,800, with potential variations based on skills, experience, and location.
• Eligibility for short-term and long-term incentives as part of total compensation.
• Comprehensive benefits package available on UKG's careers site.