- Develop and communicate a cohesive architectural vision that aligns with business goals, enabling the seamless integration of GenAI capabilities across our product suite.

Technical Leadership :

- Serve as the primary technical visionary for generative AI, providing hands-on guidance in advanced methods (e.g., transformer models, diffusion models, GANs) and setting technical standards that ensure scalability, security, and efficiency.

Cross-Functional Collaboration :

- Work closely with executive leadership, product management, data science, and engineering teams to establish and prioritize GenAI initiatives.

- Collaborate with cross-functional teams to ensure alignment on requirements and objectives, driving the infusion of AI capabilities across products.

Innovation & Research :

- 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 drive a competitive edge.

Mentorship & Culture Building :

- Mentor and influence senior engineering leaders, fostering a culture of AI excellence, thought leadership, and continuous innovation.

- Champion best practices in AI/ML development, CI/CD processes, and quality assurance to ensure high standards across the organization.

Community Engagement :

- Act as an ambassador for generative AI internally and externally, representing UKG in the AI community through publications, speaking engagements, and industry forums.

Scalable Solutions :

- Oversee the deployment of large-scale AI models, ensuring they are optimized for performance, cost, and resource efficiency in production environments.

- Establish guidelines for high-quality, production-ready AI/ML systems that can scale with business needs.

Governance & Standards :

- Define and enforce development methodologies, CI/CD standards, and architectural guidelines for AI solutions.

- Maintain documentation of architectural decisions and technical roadmaps, ensuring a sustainable foundation for future AI-driven capabilities.

Qualifications :

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.

Technical Proficiency :

- Expert-level skills in programming languages (e.g., Python, Java) and AI frameworks (e.g., TensorFlow, PyTorch).

- Strong understanding of cloud platforms (AWS, Google Cloud, Azure) and MLOps practices for large-scale model training and deployment.

AI Methodologies :

- In-depth knowledge of generative AI methodologies, including transformer models, diffusion models, GANs, large language models, and multi-modal architectures.

- Familiarity with NLP and machine learning algorithms, such as linear and logistic regression, decision trees, and clustering methods.

Industry Influence :

- Recognized thought leader in AI, with a record of publications in top-tier AI conferences/journals (e.g., NeurIPS, ICML, CVPR) and a strong network within the AI research community.

Problem-Solving & Strategy :

- Exceptional problem-solving skills and a proven ability to influence and implement long-term AI-driven strategic initiatives.