Senior Director, AI Platform Architecture

Job description

Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description At PPD, Thermo Fisher’s clinical research group (CRG), we’re using digital innovation, data science, and AI to reimagine how life-changing therapies reach patients. Our teams combine deep scientific expertise with advanced analytics, automation, and digital platforms to make research smarter, faster, and more connected. We know that innovation happens when diverse minds meet. Our Digital Science, Data, and AI professionals collaborate closely with scientists, clinicians, and operational experts to solve real-world challenges in clinical research. Alongside our partnership with Open AI, you can be part of the collaboration that will help to improve the speed and success of drug development, enabling customers to get medicines to patients faster and more cost effectively. About the Team: CRG Digital AI is the engine that translates our digital strategy into scalable, production-ready AI capabilities that drive measurable business impact. Operating in close partnership with Product, Data, and Engineering, the team embeds AI across our digital portfolio to accelerate clinical trial execution, enhance data-driven decision-making, and unlock differentiated value for our customers. Through a combination of centralized platforms, standards, and federated execution, CRG Digital AI enables rapid innovation while ensuring consistency, quality, and responsible AI practices. About the Position: Reporting to the VP, Head of Analytics and AI, the Senior Director, AI Platform Architecture is a senior leadership role within CRG Digital responsible for defining, building, and scaling the foundational AI platform that enables the rapid development, deployment, and operation of AI-enabled products and solutions across CRG. This leader owns the end-to-end AI platform strategy, architecture, and delivery model—ensuring that AI capabilities are scalable, reusable, secure, and production-ready. Operating at the intersection of Applied AI (AAI), Data Platforms, and Digital Engineering, this role serves as the backbone of CRG’s AI ecosystem—providing the tools, infrastructure, standards, and services required to accelerate AI innovation while maintaining governance, compliance, and operational excellence. The Director will enable both centralized and federated AI execution, empowering product and engineering teams to build AI solutions efficiently and consistently. Key Responsibilities: AI Platform Strategy & Ownership Define and execute the AI platform strategy and roadmap, aligned to CRG Digital and AI priorities Establish the AI platform as a shared capability layer supporting all AI-enabled products and workflows Ensure alignment with enterprise architecture, data platform (MDP), and security strategies Drive a platform-first approach to AI development, enabling reuse and scalability across domains Platform Architecture & Engineering Lead the design and development of the AI platform architecture, including: Model development, training, and deployment frameworks MLOps and LLMOps pipelines Model serving, monitoring, and lifecycle management Integration with data platforms (e.g., Snowflake, Databricks) Ensure platform supports GenAI, agentic workflows, and traditional ML use cases Establish standards for performance, scalability, reliability, and cost efficiency Reusable AI Capabilities & Tooling Build and scale reusable AI components, including: Model libraries and templates Prompt frameworks and orchestration tools Workflow automation and agent frameworks Enable rapid development through self-service tools and developer enablement Reduce duplication and accelerate time-to-market through standardization and reuse MLOps, Governance & Responsible AI Enablement Establish and operationalize AI lifecycle management practices, including: Model versioning, validation, deployment, and monitoring Performance tracking and drift detection Partner with AI Risk/Governance teams to embed compliance, security, and responsible AI principles into the platform Ensure auditability, traceability, and adherence to regulatory and enterprise standards Federated AI Enablement Provides self-service platform capabilities to AI Engineering; ensures adoption through ease-of-use and standardization Enable a federated AI model, allowing domain/product teams to build AI capabilities while leveraging centralized platform standards Provide tooling, frameworks, and guardrails to ensure consistency and quality across distributed teams Act as a central enablement layer supporting both AAI and product-aligned engineering teams Cross-Functional Integration Partner closely with: AAI (Applied AI) for solution design and AI architecture, Data Platforms for data ingestion, quality, and readiness and Digital Engineering for product integration and delivery Ensure seamless integration of platform capabilities into AI products and workflows Partner & Ecosystem Management Define and manage relationships with technology vendors and platform partners (e.g., cloud, AI tooling providers) Evaluate and integrate emerging AI technologies and tools into the platform ecosystem Optimize the balance between build vs. buy vs. partner decisions Team Leadership & Capability Building Lead a high-performing team of AI platform engineers, MLOps specialists, and platform architects Define skills, roles, and career paths for AI platform talent Drive capability building in AI engineering, platform operations, and emerging AI technologies Foster a culture of innovation, reliability, and continuous improvement Measures of Success: Adoption and utilization of the AI platform across CRG Digital teams Reduction in time-to-deploy AI solutions and increased development velocity Increased reuse of AI components and platform capabilities Strong performance of AI systems (reliability, scalability, cost efficiency) Effective implementation of AI governance and lifecycle management practices Development of a scalable and high-performing AI platform organization Qualifications: Bachelor’s degree required; advanced degree preferred (computer science, engineering, AI/ML, or related field) 12 years of experience in software engineering, data platforms, AI/ML engineering, or platform leadership roles Proven track record of building and scaling AI/ML platforms or data platforms in enterprise environments Strong understanding of AI/ML and GenAI technologies, MLOps/LLMOps practices and Cloud platforms and modern data architectures Experience operating in complex, matrixed organizations with cross-functional stakeholders Experience in regulated environments (healthcare/life sciences) preferred Knowledge, Skills, and Abilities: Deep technical and strategic understanding of AI platform architecture and operations Strong systems thinking with ability to balance innovation, scalability, and governance Ability to translate platform capabilities into business and product impact Strong leadership and team-building capabilities Excellent stakeholder management and ability to influence across Product, Data, AI, and Engineering teams Ability to operate in a fast-paced, evolving technology landscape 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 r