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

Overview

Senior Solution Architect to shape and lead the architecture of next-generation digital and AI-enabled capabilities across Pharma R&D, working closely with Submission Data and Content Generation & Reuse (including AIDCG) and contributing more broadly across Regulatory Affairs.

What you'll 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.

What you'll need

• 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.

Nice to have

• 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.

Details

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