Solution Architect - Pharma R&D

Overview

Design and deliver cloud and AI-enabled solutions for Pharma R&D, combining enterprise data and content, cloud technologies, Generative AI and agentic capabilities, working with senior architects, product teams, engineers, data scientists and domain experts.

What you'll do

• 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.

What you'll need

• 6+ years of experience in enterprise software architecture.
• 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.

Nice to have

• Exposure to pharmaceutical, clinical, regulatory or other regulated environments.
• Experience with MLOps/LLMOps, enterprise retrieval/knowledge systems or Responsible AI.
• Hands-on familiarity with GxP compliance, software validation, 21 CFR Part 11, and audit-trail implementations in pharmaceutical or healthcare software.

Details

• Location: Hyderabad.
• Shift: CET time zone.