Solution Architect - Pharma R&D

Job description

Job Responsibilities

• Define end-to-end solution architectures for complex business capabilities across R&D, clinical development, regulatory, medical affairs, commercial, pharmacovigilance, supply chain, and enterprise functions.
• Translate business and product requirements into scalable, secure, modular, and interoperable technology architectures.
• Establish and maintain enterprise information models, ontologies, taxonomies, controlled vocabularies, metadata models, and knowledge representations to create consistent understanding of pharma data across systems.
• Design solutions leveraging knowledge graphs, semantic layers, data products, data fabric/mesh principles, and metadata-driven architectures.
• Identify opportunities to embed Generative AI, LLMs, AI agents, RAG, machine learning, and intelligent automation into pharmaceutical workflows.
• Architect GenAI-enabled solutions using enterprise knowledge, domain ontologies, taxonomies, structured/unstructured data, and governed retrieval mechanisms.
• Ensure AI solutions are explainable, traceable, secure, responsible, and aligned with enterprise AI governance.
• Design integration architectures connecting systems such as clinical trial platforms, Veeva, SAP, CRM, data platforms, laboratory systems, regulatory systems, and external data sources.
• Define APIs, event-driven integrations, data flows, canonical models, and interoperability patterns across heterogeneous technology landscapes.
• Collaborate with Product, Engineering, Data Science, Data Governance, Security, Compliance, Medical, Clinical, Regulatory, and business stakeholders.
• Establish architecture principles, reference architectures, design patterns, technology standards, and reusable solution components.
• Evaluate emerging technologies and assess their applicability to pharmaceutical and life-sciences use cases.
• Ensure solutions comply with relevant GxP, privacy, security, data integrity, validation, and regulatory requirements.
• Drive architecture decisions through architecture reviews, trade-off analysis, proof-of-concepts, and technology evaluations. dentify opportunities to rationalize legacy applications and evolve toward cloud-native, API-first, data-centric, and AI-enabled architectures.
• Create architecture artifacts including context diagrams, capability maps, logical/physical architectures, data models, integration patterns, sequence diagrams, and architecture decision records.

Education / Experience

Additional Qualifications

• Strong communication and stakeholder management skills, with the ability to explain difficult or sensitive information and successfully build consensus.
• Proactive mindset to identify opportunities to enhance value and business processes, improve existing solutions, and manage technical debt.
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