AI Principal Architect II

What you will be doing
Position Summary:
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

Collaboration & Partnership

• Foster strong partnerships across business units, IT, and external vendors to align data and AI strategies with enterprise priorities.
• Act as a trusted advisor to senior leadership, translating complex technical concepts into actionable business insights.
• Facilitate cross-functional collaboration to ensure shared ownership of data-driven initiatives and seamless execution.
• Represent the data and AI architecture function in enterprise governance forums, steering committees, and strategic planning sessions.

Influence & Change Advocacy

• Champion a data-driven culture by promoting the value of analytics and AI across the organization.
• Influence stakeholders to adopt modern data and AI practices through education, storytelling, and strategic alignment.
• Lead change management efforts to support the adoption of new technologies, platforms, and processes.
• Advocate for continuous improvement and innovation in data and AI architecture to drive long-term transformation.

Typical Education/ Experience

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.
• 10+ years of experience in data architecture, analytics, and AI/ML systems.
• Proven leadership in designing enterprise-scale data platforms and AI solutions.
• Experience leading architecture teams
• Deep expertise in cloud platforms (e.g., Azure, AWS, GCP), data lakes, data warehouses, and real-time data processing.
• Strong understanding of AI/ML frameworks (e.g., TensorFlow, PyTorch), MLOps, and model deployment strategies.
• Experience with Databricks ecosystem.
• Experience with enterprise architecture frameworks (TOGAF, Zachman).
• Familiarity with data mesh, data fabric, and modern data stack concepts.
• Certifications in cloud architecture or AI/ML technologies
• Excellent communication and stakeholder management skills.
• Experience with data governance frameworks and regulatory compliance (GDPR, HIPAA, etc.)

What your background should look like
Minimum Skills, Knowledge and Ability Requirements

• Team oriented and collaborative working style.
• Growth mindset, positive attitude and strong interest in solving business challenges, adapting to a changing work environment.
• Ability to communicate effectively both orally and in writing; ability to communicate (and work) effectively with people from different technical and business backgrounds, acting as a liaison, understanding, and appreciating different perspectives and translating into terms necessary for any group or individual to understand.
• Building relationships: Establishes and maintains networks and alliances. Shares information and readily determines who to go to for relevant information. Seeks assistance and feedback in the problem-solving process. Partners with others to achieve expectations.
• Business function knowledge: Involves the key players in identifying operating needs, issues and solutions. Proposes technical plans that are aligned with business objectives and technical requirements. Takes and leads actions to enhance business function standards and performance with the participation of business and technical partners.
• Presentation skills: ability to present and discuss technical information in a manner that establishes rapport, persuades others, and establishes understanding for technical and non-technical audiences.
• Strong organizational skills; attention to detail.
• Strong interpersonal skills.
• Shows tactful discretion with difficult/sensitive information

Schedule
Full time