AI Architect Principal - AI Foundation

Summary: The AI Architect is responsible for defining the overarching strategy and architecture for artificial intelligence across the enterprise. This role establishes the principles, standards, and technology roadmap that will guide the development of all AI initiatives. They focus on creating a cohesive and future-proof AI ecosystem that enables innovation while ensuring alignment with business strategy, data governance, and enterprise architecture.

The AI Architect provides thought leadership and technical guidance to teams and senior leadership on the strategic application of AI.

• Develop and maintain the enterprise AI architecture, including reference architectures and design patterns.
• Define the strategy for the company's AI platforms, tools, and infrastructure.
• Lead the evaluation and selection of foundational AI technologies and partners.
• Provide expert consultation to business units and project teams on the art of the possible with AI.
• Govern the implementation of AI solutions to ensure they adhere to architectural standards and best practices.
• Mentor technical talent and act as a thought leader both internally and externally.
• Stay up to date with the progression of the overall AI landscape and provides inputs to ensure adoption of relevant architecture patterns.

• Strategic AI Leadership: Proven experience in a leadership capacity, defining enterprise-level AI strategy / enterprise architecture
• Develop comprehensive architecture roadmaps and governance frameworks.
• Executive Communication & Influence: Exceptional strategic thinking and communication skills, with a demonstrated ability to influence C-level executives and guide technical teams.
• Technical Architecture Expertise: Deep expertise in designing and architecting complex, scalable AI and machine learning systems, grounded in a strong understanding of data architecture, data engineering, and MLOps principles.
• Broad AI/ML Proficiency: In-depth knowledge of the AI/ML technology landscape , including in-depth understanding of major cloud platforms (GCP, AWS, Azure), industry trends, and proficiency in key domains such as LLMs, prompt engineering, Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP) , AI Agents, data management, LLM integration, DevOps, computer vision, and predictive analytics.
• Data Governance & Security: A strong command of data strategy, governance, and security principles as they apply to the development and deployment of enterprise AI solutions.

Minimum Education: Master’s degree or PhD in Computer Science, Data Science, Engineering, or related field preferred.

Minimum Experience: 8+ years of experience. Must have a proven track record of solving ambiguous business problems with novel system architectures. Experience should include designing reference architectures or reusable platforms that have been adopted by multiple teams.

Pay Transparency: The compensation listed reflects the pay range or rate of pay reasonably expected for this posted position at the posted location or locations. If this opportunity includes multiple job levels, the pay information represents the ranges for each level in that job family. Actual pay is determined by several job-related factors permitted by law and relevant to the position, including, but not limited to, experience relative to the job, tenure, market level, pay at the location for this job, performance, schedule, and work assignment.

In California, the compensation listed reflects the range or rate of pay reasonably expected for this posted position upon hire. In New Jersey, any compensable Security and Walk time will be paid to non-exempt/hourly employees at the state minimum wage.