Ai Principal Architect

Description:

The Data, Analytics, and AI Principal Architect II is a senior architect role responsible for defining and driving the strategic vision for enterprise data and AI systems. This position oversees the design and implementation of scalable, secure, and innovative data platforms and AI capabilities that empower business intelligence, advanced analytics, and machine learning across the organization. The ideal candidate will blend deep technical expertise with strategic foresight to lead a team of architects and collaborate cross-functionally to unlock the full potential of data and AI.

The ideal candidate will possess a rare blend of technical mastery, strategic vision, and leadership acumen. They should demonstrate advanced proficiency in enterprise data architecture, cloud platforms, and AI/ML technologies, with a proven ability to design scalable solutions that support complex business needs. Strong communication and stakeholder management skills are essential for guiding cross-functional teams and aligning technical initiatives with organizational goals. A solid understanding of data governance, privacy regulations, and interoperability frameworks is critical. Above all, this leader must be innovative, collaborative, and results-driven; committed to harnessing data and AI to drive transformation and deliver measurable impact.

In this role you will act as an advisor for various complex projects and initiatives and taking full ownership of all necessary architectural artifacts, high-level designs, proof of concepts (POCs), and deployment support for large to complex data, analytics, and AI solutions. You will play a pivotal role in defining the building blocks for future-state architecture and creating a roadmap for realizing these goals. Key responsibilities include defining architectural standards, ensuring data governance and security compliance, evaluating emerging technologies, and guiding cross-functional teams in the integration of data and AI capabilities. This role also plays a critical role in aligning technical solutions with organizational goals, driving operational efficiency, and enabling data-driven decision-making across the enterprise.

You will thrive on bringing innovative approaches validated by quality research, industry insights, and proof of concepts supporting the suggested technology or architecture solution blueprint. Furthermore, you will possess robust expertise in ML/AI capabilities. This diverse knowledge will empower you to recommend breakthrough improvements across the entire data and analytics ecosystem, ensuring the integration of AI/ML capabilities to enhance analytics processes and outcomes.

Primary Duties & Responsibilities
 

• Develop and own the enterprise data and AI architecture roadmap aligned with business goals.
• Lead the design and implementation of scalable data platforms, analytics solutions, and AI/ML infrastructure.
• Define standards and best practices for data governance, metadata management, and model lifecycle management.
• Partner with engineering, product, and business teams to ensure seamless integration of data and AI capabilities.
• Evaluate emerging technologies and trends in data, analytics, and AI to inform strategic decisions.
• Oversee architectural reviews, technical assessments, and solution design for complex data initiatives.
• Ensure compliance with data privacy, security, and regulatory requirements.
• Build and mentor a high-performing team of data and AI architects.
   

AI/ML Integration
 

• Model development and deployment using frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Familiarity with cloud-based ML platforms, such as AWS SageMaker, Azure Foundry, or Google AI Platform, Mosaic AI
• Experience in utilizing tools like MLflow for managing the ML lifecycle, including experimentation, reproducibility, and deployment
• Knowledge of natural language processing (NLP) and/or reinforcement learning techniques as applicable to business use cases
• Ability to integrate advanced analytics and AI/ML models into existing data workflows, ensuring seamless access and usability
   

Software Evaluations & Innovation
 

• Lead the assessment and selection of data and AI software platforms, tools, and frameworks to ensure alignment with architectural standards and business needs.
• Establish a formal process for evaluating vendor solutions, open-source technologies, and proprietary platforms for scalability, interoperability, and long-term viability.
• Drive innovation by piloting new technologies and proof-of-concept initiatives that explore advanced analytics, generative AI, and automation opportunities.
• Collaborate with R&D and innovation teams to identify use cases where emerging software can deliver competitive advantage or operational efficiency.
• Maintain a technology radar to track and communicate the maturity and relevance of new tools and platforms across the data and AI landscape