1 day ago
Hyderābād, IndiaSenior
Responsibilities
- Define end-to-end solution architectures for complex pharmaceutical and enterprise business capabilities.
- Translate business and product requirements into scalable, secure, modular and interoperable architectures.
- Establish information models, ontologies, taxonomies, controlled vocabularies, metadata models and knowledge representations.
- Design solutions using knowledge graphs, semantic layers, data products, data fabric or mesh principles and metadata-driven architectures.
- Architect GenAI-enabled solutions using enterprise knowledge, governed retrieval, LLMs, AI agents and RAG.
- Design integrations across clinical trial, Veeva, SAP, CRM, laboratory, regulatory and external data systems.
- Define APIs, event-driven integrations, data flows, canonical models and interoperability patterns.
- Establish architecture principles, reference architectures, design patterns, technology standards and reusable components.
- Evaluate emerging technologies, lead architecture reviews and proofs of concept, and manage technical debt.
- Ensure solutions meet GxP, privacy, security, data integrity, validation and regulatory requirements.
- Create architecture artifacts including context diagrams, capability maps, logical and physical architectures, data models, sequence diagrams and architecture decision records.
- Collaborate with Product, Engineering, Data Science, Data Governance, Security, Compliance, Medical, Clinical, Regulatory and business stakeholders.
Requirements
- 5–8+ years of experience in Solution Architecture, Enterprise Architecture, Data Architecture or Technology Architecture.
- Strong understanding of pharmaceutical or 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, taxonomies, ontologies, 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 AWS, Azure or 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 communication and stakeholder-management skills, including the ability to explain architecture concepts to technical and non-technical audiences and build consensus.
- Proactive mindset focused on improving business processes, enhancing solution value and managing technical debt.
Tech Stack
Categories
Solutions Engineering
About Roche
Roche is a Swiss healthcare company that develops and sells prescription pharmaceuticals and in vitro diagnostic systems for hospitals, laboratories, and clinicians. Its business spans two core divisions—Pharmaceuticals and Diagnostics—with strengths in oncology, immunology, neuroscience, infectious diseases, and diabetes care. Founded in 1896 and headquartered in Basel, Switzerland, Roche also advances personalized healthcare by pairing therapies with companion diagnostics.