Translate portfolio and product strategy into actionable solution architectures spanning data, AI, application, and integration layers. Define end-to-end architectures that connect SaaS/commercial products, enterprise platforms, and custom engineering components into cohesive solutions. Ensure architectures enable secure, stable, scalable, maintainable and cost efficient.
Own and maintain a clear, evolving view of scientific and informatics capabilities, and how they map to existing and future digital solutions. Ensure these capabilities are consistently layered across solutions, with clear boundaries, responsibilities, and interactions, enabling a coherent and interoperable ecosystem.
Design and govern integration patterns across heterogeneous ecosystems, including APIs, event-driven architectures, and shared data services. Enable interoperability across data platforms, AI services, laboratory systems, and external partner environments. Ensure solutions support scalability to thousands of users and high-volume data processing.
Act as the primary interface between delivery segment teams and engineering/platform teams. Translate research and scientific workflows into actionable technical designs. Provide clear architectural guidance that is consumable by engineering teams while ensuring alignment with domain needs.
Influence & Architectural Governance
Provide architectural oversight and governance, ensuring solutions align with standards, compliance, and strategic objectives. Promote reuse, consistency, and adoption of architectural standards across teams. Ensure consistency in how scientific and informatics capabilities are represented, reused, and governed across solutions.
Collaboration & Delivery Enablement
Partner with product, data, AI, and engineering leaders to shape roadmaps and delivery sequencing. Balance near-term delivery requirements with long-term sustainability and architectural integrity. Enable high-quality delivery through pragmatic, context-specific guidance.
Minimum 5+ years’ experience in the life sciences / pharmaceutical industry
Advanced degree in a relevant field (e.g., Life Sciences, Biomedical Sciences, Engineering, Computer Science, or related discipline)
Technical & Architectural Expertise
Strong experience in solution and platform architecture across cloud-native, distributed, and data-intensive systems. Deep understanding of integration patterns, APIs, microservices, and event-driven architectures. Familiarity with AI/ML model integration, agentic systems and operationalization within enterprise environments.
Research Domain Experience
Experience working in scientific or research-driven environments such as biomedical research or life sciences. Ability to quickly understand domain workflows and translate them into digital, data, and AI-enabled solutions.
Excellent communication and influence skills, with the ability to operate across domain experts, delivery teams, and engineering teams. Ability to translate complex technical concepts into clear, actionable guidance.
Strategic & Systems Thinking
Ability to connect solution architecture decisions to broader delivery strategy, data strategy, AI strategy, and digital transformation initiatives. Strong systems thinking to balance scalability, reusability, and delivery speed.
