Senior Director, AI Platform Architecture
Thermo Fisher Scientific · Massachusetts, United States · 1 mo ago
RemoteRemoteScience$168k–$278k/yrFull-time
About the role
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.
Responsibilities
- 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
- 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)
- Establish standards for performance, scalability, reliability, and cost efficiency
- 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
- 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
- Provide self-service platform capabilities to AI Engineering
- Ensure adoption through ease-of-use and standardization
- 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
- 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
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