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Cencora · 22 hours ago

AI Principal Architect II

United, PA

Full-time

Onsite

Lead/Staff

10+ years exp

Cencora is dedicated to creating healthier futures and is seeking a Data, Analytics, and AI Principal Architect II to define and drive the strategic vision for enterprise data and AI systems. This role involves overseeing the design and implementation of scalable data platforms and AI capabilities, leading a team of architects, and ensuring alignment with organizational goals to enhance data-driven decision-making.

Emergency MedicineEnterprise SoftwareHealth CareMedicalPharmaceutical

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

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

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

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

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

Qualification

Enterprise data architectureAI/ML technologiesCloud platformsData governanceData lakesData warehousesMLOpsModel deployment strategiesNatural language processingTeam orientedCommunicationInterpersonal skillsPresentation skillsOrganizational skills

Required

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.)

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