Solution Architect - Pharma R&D

Overview

Design business-driven, standards-based, future-ready solutions for a specific solution context, managing non-functional requirements and fitness functions, and maintaining the product's technology roadmap with technical oversight of product teams.

What you'll do

• 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.
• Identify 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.

What you'll need

• 5 - 8+ years of experience in Solution Architecture, Enterprise Architecture, Data Architecture, or Technology Architecture.
• Strong understanding of Pharma / Life Sciences business processes and technology landscapes.
• Experience designing enterprise-scale solutions involving cloud, APIs, data platforms, integration, microservices, and distributed systems.
• Strong understanding of data modeling, metadata management, taxonomy, ontology, semantic modeling, and knowledge graphs.
• Hands-on understanding of GenAI, LLMs, RAG, AI agents, embeddings, vector databases, prompt engineering, and AI orchestration.
• Experience translating business problems into AI-enabled products and enterprise solutions.
• Understanding of data governance, master data management, data quality, lineage, and interoperability.
• Familiarity with platforms such as AWS/Azure/GCP, Databricks, Snowflake, knowledge graph technologies, API platforms, and enterprise integration platforms.
• Understanding of regulated environments, including GxP, validation, auditability, privacy, security, and data integrity.
• Strong stakeholder management and communication skills, with the ability to communicate architecture concepts to both technical and non-technical audiences.
• 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.

Details

• Location: Hyderabad.
• Shift: CET time zone.