Level

Roche

Solution Architect Submission Data and Content Generation & Reuse (AIDCG) - Pharma R&D

AI in this role

Lead the architecture of next-generation digital and Generative AI-enabled capabilities across Pharma R&D.

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ragllm-integrationml-opsai-evaluationai-safetysolution-architecturesystem-designdata-governancecloud-architecture

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

The Position

Roche Digital Technology is looking for a Senior Solution Architect to help shape and lead the architecture of next-generation digital and AI-enabled capabilities across Pharma R&D.

You will work closely with Submission Data and Content Generation & Reuse, including initiatives such as AIDCG, while contributing more broadly across Regulatory Affairs and related Pharma R&D capabilities.

We are looking for an architect who can connect business strategy, modern technology and engineering execution — establishing long-term technical direction while remaining close enough to implementation to ensure solutions are scalable, secure, reliable and production-ready.


What you will do

  • Own end-to-end architecture for complex products, platforms and cross-product capabilities from discovery through production.
  • Translate business outcomes and workflows into scalable, secure and maintainable technical architectures.
  • Shape target architectures, technology roadmaps, reusable patterns and reference architectures.
  • Architect Generative AI and agentic AI solutions, including orchestration, retrieval and grounding, tool integration, human-in-the-loop, evaluation, guardrails and observability.
  • Lead cloud architecture decisions across applications, APIs and integrations, data, identity, security, resilience and operational architecture.
  • Define and govern key non-functional requirements including availability, scalability, performance, security, recoverability and cost.
  • Design integration across enterprise platforms, data and content systems while ensuring appropriate traceability, provenance and access control.
  • Lead architecture reviews, evaluate technical trade-offs and guide teams through complex engineering decisions.
  • Evaluate emerging technologies and vendors based on business fit, maturity, security, cost and long-term sustainability.
  • Act as a trusted technical advisor to senior stakeholders while mentoring architects and engineers and strengthening architecture practices across teams.

Who you are

Required qualifications

  • 10+ years of experience in enterprise software architecture, with at least 2+ years designing and deploying production-grade Generative AI / Agentic systems at scale
  • Strong experience with cloud-native and distributed systems architecture, preferably AWS.
  • Demonstrated experience designing or delivering production Generative AI or agentic AI solutions.
  • Strong understanding of modern AI patterns such as LLM integration, RAG/knowledge grounding, agent orchestration, tool use, state/context management, evaluation and human-in-the-loop.
  • Strong understanding of APIs, integration patterns, application and data architecture, security and modern software engineering.
  • Experience with CI/CD, infrastructure as code, DevSecOps, observability and production operations.
  • Demonstrated ability to make architecture trade-offs across reliability, scalability, security, performance, cost and delivery speed.
  • Ability to translate ambiguous business problems into clear architecture decisions and executable technical direction.
  • Strong technical leadership, stakeholder influence, communication and mentoring skills.
  • Strong sense of ownership and accountability for technical outcomes.

Preferred qualifications

  • Experience in pharmaceutical R&D, clinical development, regulatory technologies or other regulated environments.
  • Hands-on familiarity with GxP compliance, software validation, 21 CFR Part 11, and audit-trail implementations in pharmaceutical or healthcare software."
  • Experience with enterprise knowledge/retrieval architectures or MLOps/LLMOps.
  • Familiarity with Responsible AI, AI governance, validation, provenance and auditability.


Technology environment

Our landscape includes AWS, cloud-native services, Python, enterprise APIs, modern LLMs, agentic orchestration, retrieval and knowledge technologies, AI evaluation and observability, and modern DevSecOps.

We value architectural depth and adaptability over expertise in any single tool or vendor.

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 rate this

Solution Architect Submission Data and Content Generation & Reuse (AIDCG) - Pharma R&D at Roche rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

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

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGLLM IntegrationML OpsAI EvaluationAI SafetySolution ArchitectureSystem DesignData Governance

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How have you integrated a large language model into a production application?
  3. How do you monitor a model once it's live, and how do you know it needs retraining?
  4. How do you decide that one model's output is better than another's for a given task?
  5. How do you think about the risk of an AI system in this kind of role failing silently?

Adapt your resume

  • List these exact terms on your resume: RAG, LLM Integration, ML Ops, AI Evaluation, and AI Safety. 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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