Solution Architect - Pharma R&D

F. Hoffmann-La Roche AG; Hyderabad; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

F. Hoffmann-La Roche AG in Hyderabad (India) is seeking a seasoned Solution Architect to design end-to-end architectures for cross-functional pharma workflows, with emphasis on cloud-native, API-first, and data-centric approaches.

You will translate business requirements into scalable, secure architectures, establish metadata models, integrate AI/GenAI capabilities, and collaborate with product, engineering, data science, and regulatory stakeholders to ensure GxP compliance and governance.

Qualifications

• 5–8+ years of experience in Solution Architecture, Enterprise Architecture, Data Architecture, or Technology Architecture.
• 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.

Responsibilities

• Define end-to-end solution architectures for complex 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 architectures.
• Establish enterprise information models, ontologies, taxonomies, controlled vocabularies, and metadata representations.
• Design solutions leveraging knowledge graphs, semantic layers, data products, data fabric/mesh principles, and metadata-driven architectures.
• Identify opportunities to embed GenAI, 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.

Skills

Cloud architecture

Data modeling

GenAI & LLMs

APIs & Microservices

Knowledge graphs

Data governance

Stakeholder communication

GxP & regulated env

Tools

AWS

Azure

GCP

Databricks

Snowflake

API platforms

Job description

### A posição****Job description******The Solution Architect focuses on designing business-driven, standards-based, and future-ready solutions within a specific solution context. In this role, you will design solutions that meet product requirements, business priorities, and enterprise standards while managing non-functional requirements (NFRs) and fitness functions. You will develop and maintain the product's technology roadmap, provide technical oversight to product teams, and evaluate new technologies to continuously improve existing solutions and manage technical debt.******Description of the area********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.******Qualifications********Education / Experience***** **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.******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.**