Solution Architect - Pharma R&D

AI in this role

ragai-agentsml-opsai-evaluationai-safety

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

We are looking for a technically strong Solution Architect who is excited about building modern cloud and AI-enabled solutions for Pharma R&D.

You will work with senior architects, product teams, engineers, data scientists and business experts to design and deliver solutions that combine enterprise data and content, cloud technologies, Generative AI and emerging agentic capabilities.

This role is suited to someone with strong engineering and architecture foundations who can own architecture for defined solutions and grow into broader architecture responsibility over time.

The Opportunity

As a Solution Architect, you will:

Design end-to-end solution architectures for products, use cases and technical capabilities, working with senior architects on broader cross-product decisions.
Translate business and technical requirements into practical architectures across applications, APIs, integration, cloud, data, security and operational considerations.
Design and contribute to Generative AI and agentic solutions, including LLM applications, retrieval and grounding, agentic workflows, tool integration and human-in-the-loop patterns.
Apply strong cloud engineering principles across services, APIs, data stores, identity and access management, resilience and observability.
Define key non-functional requirements, interfaces, data flows and architecture decisions.
Contribute to evaluation, monitoring, guardrails, traceability and security for AI-enabled applications.
Participate actively in architecture reviews, prototypes, technical spikes and implementation discussions.
Help establish reusable architecture patterns and components across teams.
Collaborate closely with engineers, data scientists, product teams and domain experts from solution discovery through deployment and production.
Identify technical risks early, communicate clearly and take ownership for helping teams resolve them.

Who You Are

You combine strong technical fundamentals with architectural thinking, curiosity and a desire to grow into broader technical leadership.

Required experience

6+ years of experience in enterprise software architecture, with at least 1+ years designing and deploying production-grade Generative AI / Agentic systems at scale
Good practical understanding of cloud-native architecture, preferably AWS.
Practical experience building or integrating Generative AI / LLM-enabled applications.
Understanding of modern AI patterns such as RAG, vector/semantic search, agentic workflows, tool/function calling, prompt/context management and AI evaluation.
Strong understanding of APIs, integration patterns, distributed applications, data stores and security.
Familiarity with containers, CI/CD, infrastructure as code, monitoring and observability.
Ability to consider reliability, scalability, performance, security and cost when making technical decisions.
Strong analytical, problem-solving, communication and collaboration skills.
Strong ownership and accountability for technical outcomes.
Demonstrated curiosity and ability to stay current with developments in Generative AI, agentic systems, cloud and modern software engineering.

Preferred experience

Exposure to pharmaceutical, clinical, regulatory or other regulated environments, or experience with MLOps/LLMOps, enterprise retrieval/knowledge systems or Responsible AI would be beneficial.

Hands-on familiarity with GxP compliance, software validation, 21 CFR Part 11, and audit-trail implementations in pharmaceutical or healthcare software.

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.

Experience with the exact technologies we use is not required. We value strong technical fundamentals and the ability to learn and adapt as the technology landscape evolves.

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 - Pharma R&D at Roche rates 67 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.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ 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.

Key facts

Solution Architect - Pharma R&D is an open job at Roche.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Hyderabad.
The job was posted on October 6, 2026.
Seniority: senior.
Applications are handled by Roche. Apply on Roche

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

RAGAI AgentsML OpsAI EvaluationAI Safety

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
How do you monitor a model once it's live, and how do you know it needs retraining?
How do you decide that one model's output is better than another's for a given task?
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, AI Agents, 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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