Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere. Apply today! Job Details 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.) 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 What Cencora offers We provide compensation, benefits, and resources that enable a highly inclusive culture and support our team members' ability to live with purpose every day. In addition to traditional offerings like medical, dental, and vision care, we also provide a comprehensive suite of benefits that focus on the physical, emotional, financial, and social aspects of wellness. This encompasses support for working families, which may include backup dependent care, adoption assistance, infertility coverage, family building support, behavioral health solutions, paid parental leave, and paid caregiver leave. To encourage your personal growth, we also offer a variety of training programs, professional development resources, and opportunities to participate in mentorship programs, employee resource groups, volunteer activities, and much more. For details, visit https://www.virtualfairhub.com/cencora Full time Equal Employment Opportunity Cencora is committed to providing equal employment opportunity without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, age, disability, veteran status or membership in any other class protected by federal, state or local law. The company's continued success depends on the full and effective utilization of qualified individuals. Therefore, harassment is prohibited and all matters related to recruiting, training, compensation, benefits, promotions and transfers comply with equal opportunity principles and are non-discriminatory. Cencora is committed to providing reasonable accommodations to individuals with disabilities during the employment process which are consistent with legal requirements. If you wish to request an accommodation while seeking employment, please call 888.692.2272 or email hrsc@cencora.com. We will make accommodation determinations on a request-by-request basis. Messages and emails regarding anything other than accommodations requests will not be returned Affiliated Companies Affiliated Companies: AmerisourceBergen Services Corporation

• Design scalable AI architectures for customer use cases in line with enterprise and security standards • Lead implementation of AI software components such as model serving, orchestration, retrieval, and integrations • Run time-bound proofs of value to demonstrate business outcomes quickly and clearly • Help migrate AI workloads between cloud, on-premises, and hybrid environments on Dell infrastructure • Enable customer engineers and platform teams to support and extend solutions after handover • Design, configure, and implement AI solution stacks, including model serving, orchestration, retrieval pipelines, vector stores, and related components • Select practical tools and patterns to avoid tooling sprawl and deliver working prototypes and PoVs tied to clear success measures • Lead PoV sprints (typically a few weeks): refine scope, build and iterate on solutions, and present outcomes and recommendations to stakeholders • Plan and execute cloud-to-on-prem and hybrid migration patterns for AI workloads onto Dell infrastructure, optimizing performance, reliability, and security • Take shared responsibility for production readiness and early production stability, including monitoring, performance optimization, and issue triage • Work closely with AI Data Specialists to define and consume AI-ready data pipelines that support performance and reliability • Collaborate with AI Strategists and Enterprise Architects to align technical scope with business outcomes and target-state architectures • Provide documentation, runbooks, and knowledge transfer to customer teams, and contribute to Dell AI Factory reference architectures and playbooks • Mentor other technical team members on AI architecture patterns, Dell AI infrastructure capabilities, and responsible AI practices

Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description The Clinical Research Group (CRG) of Thermo Fisher Scientific delivers industry-leading clinical trial services to pharmaceutical, biotechnology, and medical device organizations. CRG Digital is an enterprise-wide digital function dedicated to accelerating CRG’s transformation into the most digitally enabled CRO in the industry. CRG Digital leads the strategy, governance, development, and lifecycle management of digital, data, and AI products across the organization. Our mission is to power clinical development with modern digital capabilities, improving operational efficiency, enhancing customer experience, unlocking insights from data, and enabling next-generation clinical innovation. Position Summary We are seeking a highly motivated AI Engineer to help design, build, deploy, and optimize AI solutions that advance CRG’s digital strategy. In this role, you will design, implement, and optimize AI models that support data analysis, automation, and innovation within clinical research and development operations. You’ll collaborate with data scientists, software engineers, and domain experts to translate business needs into scalable, intelligent solutions. The ideal candidate will be proficient in applying statistics, programming, data modeling, simulation, and advanced mathematics to business questions, with a specific focus on Generative AI. Proven experience with exploratory data analysis techniques, machine learning algorithms (including generative models), model validation techniques, and data visualization techniques. Strong knowledge in technical areas such as SQL, Python, Spark, Jupyter, and associated packages and libraries, specifically tailored to Generative AI. This is a remote position in North Carolina. Responsibilities: AI and Machine Learning Development - Design, develop, and deploy machine learning and generative AI models to support CRG Digital priorities including predictive analytics, text/NLP solutions, automation, and intelligent decision support. - Apply statistics, programming, data modeling, simulation, and advanced mathematics to business problems. - Evaluate and optimize model performance using appropriate validation metrics and techniques. - Build reusable model pipelines, APIs, and components for scalable AI product deployment. Data Engineering and Data Management - Preprocess, clean, transform, and integrate structured and unstructured datasets from clinical and operational sources. - Build and maintain ETL/data workflows that support ML and generative AI workloads. - Work with relational, document, columnar, graph, and object store systems; design schemas for AI and analytics use cases. - Ensure data quality, reproducibility, lineage, and governance compliance. Digital Product Integration and Lifecycle Management - Collaborate with software engineering and platform teams to integrate AI models into production systems with appropriate monitoring and observability. - Support documentation, traceability, and regulatory readiness (e.g., auditability, GxP considerations). - Contribute to CRG Digital’s product development lifecycle including discovery, prototyping, testing, deployment, and iteration. Innovation, Partnerships, and Enablement - Stay current on emerging AI and ML technologies, evaluating opportunities for CRG Digital roadmaps. - Contribute to an innovative ecosystem involving external partners and technology collaborators. - Support internal digital and AI upskilling through documentation, best practices, and knowledge sharing. Tools, Technologies, and Platforms Programming: Python, SQL, Spark Libraries and Frameworks: TensorFlow, PyTorch, Keras, scikit-learn, LangChain/LangGraph, OpenAI/other LLM SDKs Data Tools: Pandas, NumPy, Jupyter Cloud and Platforms: Databricks, AWS, Azure GCP; S3 or Azure Blob Storage Version Control: Git/GitHub Education and Experience: - Bachelor's degree or equivalent and relevant formal academic/vocational qualification - Master's degree preferred. - Previous experience in machine learning, AI model development, or data science that provides the knowledge, skills, and abilities to perform the job (comparable to 2+ years). - In some cases, an equivalency, consisting of a combination of appropriate education, training, and/or directly related experience, will be considered sufficient for an individual to meet the requirements of the role. Knowledge, Skills and Abilities: - Proficiency in modern SQL, Python, Spark, and associated AI/ML packages. - Experience with generative AI, large language models, NLP, prompt engineering, and LLMOps best practices. - Strong exploratory data analysis skills: ability to validate, visualize, and communicate model behavior. - Experience with cloud architecture, distributed computing, and modern ML platforms. - Familiarity with data governance, data security, and compliance requirements (preferably in a regulated or clinical environment). - Ability to manage multiple priorities in a matrixed environment. - Excellent analytical thinking, problem-solving, and communication skills. - Ability to work independently with minimal supervision and collaborate effectively with cross-functional teams. At Thermo Fisher Scientific, we are committed to fostering a healthy and harmonious workplace for our employees. We understand the importance of creating an environment that allows individuals to excel. Please see below for the required qualifications for this position, which also includes the possibility of equivalent experience: - Able to communicate, receive, and understand information and ideas with diverse groups of people in a comprehensible and reasonable manner. - Able to work upright and stationary for typical working hours. - Ability to use and learn standard office equipment and technology with proficiency. - Able to perform successfully under pressure while prioritizing and handling multiple projects or activities. - May require as-needed travel (0-20%). Location: Remotely based in North Carolina, no relocation sponsored. *Must be legally authorized to work in the United States without sponsorship. *Must be able to pass a comprehensive background check, which includes a drug screening (US). The US annual salary range estimated for this position in North Carolina is $85,000 - $95,000 USD. This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. We offer a comprehensive Total Rewards package that our U.S. colleagues and their families can count on, which includes: - A choice of national medical and dental plans, and a national vision plan, including health incentive programs - Employee assistance and family support programs, including commuter benefits and tuition reimbursement - At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, and short- and long-term disability in accordance with company policy - Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan - Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount For more information on our benefits, please visit: https://jobs.thermofisher.com/global/en/total-rewards

At IMO Health, we combine strengths in software development, artificial intelligence, and clinical expertise to create AI-driven solutions that enhance access to reliable health information, support clinical decision-making, and improve patient outcomes. We are seeking a Staff AI / MLOps Engineer to join our Software Engineering organization, owning the end-to-end machine learning lifecycle for production AI systems. This role is responsible for designing, building, deploying, operating, and evolving AI-powered systems that are scalable, reliable, observable, and maintainable in real-world clinical environments. This is a technical leadership role focused on operational excellence and architectural rigor. The ideal candidate is a hands-on engineer with deep experience across software engineering, MLOps, DevOps, cloud infrastructure, and data systems, capable of owning ML systems from initial design through long-term production operation, monitoring, retraining, and retirement. You will partner closely with data scientists, product teams, and platform engineers to ensure AI models successfully transition from research to durable, production-grade systems. WHAT YOU’LL DO: - Own the full ML lifecycle, including data ingestion, training, validation, deployment, monitoring, retraining, and retirement. - Transition AI/ML prototypes into scalable, production-ready systems with CI/CD pipelines, automation, and observability. - Lead system design and architecture discussions, providing guidance on ML systems, MLOps, and AI infrastructure. - Develop and maintain AI-driven applications and inference services, optimizing for performance, scalability, reliability, and cost. - Integrate LLMs, generative AI, and NLP solutions into IMO Health products, focusing on unstructured clinical data. - Implement monitoring, alerting, logging, and dashboards to ensure model quality, detect drift, and maintain operational SLAs. - Build, maintain, and optimize CI/CD pipelines, automation scripts, and Infrastructure-as-Code for production ML systems. - Apply containerization (Docker, Kubernetes) and cloud infrastructure best practices to manage production environments. - Mentor and guide engineers, enforce technical standards, and drive reduction of technical debt. - Conduct root cause analysis of production defects and implement durable fixes. - Advocate for non-functional requirements (availability, scalability, reliability, maintainability) and design systems accordingly. - Collaborate cross-functionally with Product, Data Science, Architecture, and Engineering teams to align AI solutions with business goals. WHAT YOU’LL NEED: - 8+ years of professional experience in software engineering, AI/ML engineering, or related roles, building and operating production-grade systems. - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience). - Strong foundation in computer science fundamentals (data structures, algorithms, design patterns, operating systems, networking). - Expert-level coding skills in Python or Java, with a strong emphasis on production-quality software engineering practices. - Hands-on experience owning ML systems in production, including deployment, monitoring, retraining, and optimization. - Experience designing and operating CI/CD pipelines, automation, and observability for ML systems. - Deep experience with cloud platforms (AWS or Azure), containerization, and Infrastructure-as-Code. - Experience with MLOps tools and workflows (e.g., MLflow, SageMaker, Kubeflow). - Experience integrating and deploying LLMs, generative AI, and agentic systems in production environments. - Working knowledge of NLP concepts (tokenization, embeddings, classification, sequence modeling); healthcare exposure is a plus. - Experience with Elasticsearch and vector databases for embedding-based search and retrieval. - Proven ability to translate business needs into scalable, reliable technical solutions, balancing technical debt and delivery velocity. - Strong system design skills for high-performance, distributed, and scalable systems. - Excellent communication and collaboration skills across cross-functional, distributed teams. - Self-starter who can operate autonomously and own complex systems end to end.  NICE TO HAVE: - Experience with clinical or healthcare AI applications. - Familiarity with Hugging Face, PyTorch, TensorFlow, or other modern ML frameworks. - AWS Associate-level certification (Machine Learning Engineer or Solutions Architect). $170,000 - $240,000 a year Compensation at IMO Health is determined by job level, role requirements, and each candidate’s experience, skills, and location. The listed base pay represents the target for new hires with individual compensation varying accordingly. These figures exclude potential bonuses or sales incentives, which may also be part of the total compensation package. Our recruiter will provide additional details during the hiring process. IMO Health also offers a comprehensive benefits package. To learn more, please visit IMO Health’s Careers Page.