Director of AI Engineering – Vaccine R&D Operations Enablement

POSITION SUMMARY

We are seeking to identify a Director of AI Engineering to lead AI-driven transformation across Vaccine R&D Operations. You will focus on applying AI automation, and advanced analytics in process-intensive, highly regulated environments, spanning laboratory operations, development execution, quality systems, business processes, and external partner engagement.

Embedded within Vaccines R&D, you’ll partner with scientific, development, quality, informatics, finance, and operational leaders to translate real‑world operational complexity into scalable, production‑grade AI systems that improve execution speed, decision quality, compliance readiness, and overall R&D experience.

What you’ll do:

Lead AI enablement of Vaccine R&D operations

• Define and deliver AI solutions that support process-heavy lab and office workflows, including experiment tracking, documentation, handoffs, and operational reporting.
• Drive automation of manual and repetitive activities to improve speed, quality, consistency, and compliance across vaccine development.

Strengthen operational decision-making

• Develop predictive, optimization, and scenario-based models to support resource planning, capacity management, timeline forecasting, and risk trade-offs.
• Develop dashboards and decision-support tools that translate complex operational data into actionable insights for R&D and leadership teams.

Enable regulated, inspection-ready AI systems

• Design AI solutions aligned with GxP expectations, data integrity standards, and inspection readiness, supporting deviation monitoring, CAPA trending, documentation completeness, data genealogy, and audit preparedness.

• Establish governance models covering model validation, versioning, explainability, monitoring, and lifecycle management in regulated environments.

Optimize development planning execution

• Build AI‑enabled capabilities for development planning, milestone tracking, dependency management, and execution risk forecasting across the vaccine development lifecycle
• Lead process optimization and reengineering initiatives, using AI, automation, and data-driven methods to simplify workflows and reduce cycle times.

Engineer and scale production-grade AI platforms

• Architect and deploy robust, production-ready ML and analytics pipelines with appropriate governance, reproducibility, and monitoring.
• Scale AI solutions in cloud and/or High-Performance Computing environments, ensuring reliability, security, and seamless integration with existing R&D, financial, and operational systems.

Partner and lead across disciplines

• Act as a strategic bridge between technical teams and scientific, operational, quality, and business stakeholders to ensure adoption and measurable value.
• Mentor engineers and operational partners, raising AI and data literacy across vaccine R&D.
• Champion best practices in MLOps, software engineering, and AI system lifecycle management.

What you’ll bring

Basic Qualifications:

• PhD in Computer Science, Machine Learning, Data Science, Software Engineering, AI, or a related discipline and a minimum of 5 years of applied analytical experience with demonstrated impact in operations, automation, business analytics, or decision support OR
• Master’s in Computer Science, Machine Learning, Data Science, Software Engineering, AI, or a related discipline and a minimum of 7 years of applied analytical experience with demonstrated impact in operations, automation, business analytics, or decision support
• Minimum 2 years of AI/ML experience in a relevant domain
• Strong understanding of process-heavy environments, ideally within R&D, clinical operations or large-scale regulated organizations
• Expertise in predictive modeling, optimization, automation, generative AI, and ML system design.
• Strong programming skills in Python and modern ML frameworks (e.g., PyTorch, TensorFlow), plus experience scaling models in cloud and/or HPC environments.
• Experience collaborating across scientific, operational, quality, and business teams, translating complex needs into practical AI solutions.
• Clear communication skills

Preferred Qualifications:

• Experience in life sciences, pharma, R&D, clinical operations, or other regulated industries.
• Financial and business experience supporting budgets, forecasting, vendor management, or portfolio analytics.

Work Location Assignment: This is a hybrid role requiring you…