Level

Roche

Solution Architect - Pharma R&D

AI in this role

databricks
prompt-engineeringragai-agentsai-automation

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections,  where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

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.

Shift: CET time zone

#Hyderabad2026

 

 

Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.


Let’s build a healthier future, together.

Roche is an Equal Opportunity Employer.

How we score this

Solution Architect - Pharma R&D at Roche scores 71 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 3. The daily work is on or around AI systems, without necessarily building the model: remove AI and the job is hollow.

  1. AI Level 480 to 100
  2. AI Level 360 to 79
  3. AI Level 240 to 59
  4. AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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Skills and AI tools this role asks for

Prompt EngineeringRagAI AgentsAI AutomationDatabricks

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How do you decide when an AI agent can act on its own versus asking for approval first?
  4. Tell me about a workflow you automated with AI tools, end to end.
  5. Walk me through how you've used Databricks in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering, Rag, AI Agents, AI Automation, and Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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