AI Architect - RDT Artificial Intelligence

Roche is a leading healthcare and diagnostics company with over 100,000 employees globally, dedicated to advancing science to ensure access to healthcare and innovative solutions for generations to come. The company’s efforts result in over 26 million people treated with its medicines and more than 30 billion tests conducted using its diagnostics products.

• 10+ years experience in software architecture and engineering with 3+ years leading enterprise AI or ML platform initiatives.
• Proven experience architecting core middleware and backend systems for scalable data routing and observability.
• Experience delivering high-performance technical environments within regulated industries such as Biotech, Pharma, or Healthcare.
• Deep understanding of Large Language Models (LLMs), RAG pipelines, agentic workflows, and Model Context Protocol (MCP).
• Expertise in cloud-native paradigms, container orchestration, Infrastructure as Code (IaC), and GPU compute orchestration.
• Strong skills in vector similarity search engines, cloud data warehouses, and event-driven data pipelines.
• Advanced proficiency in Python and enterprise DevOps including CI/CD, containerized workload monitoring, and API security.
• Proven executive presence with ability to influence senior leadership and federate architectural leadership.
• Educational background with B.Sc., M.Sc., or Ph.D. in Computer Science, Software Engineering, Artificial Intelligence, or related quantitative fields.
• English language proficiency at C1+ level.

Enterprise AI Architecture & Taxonomy:

• Architect and evolve enterprise AI reference architecture based on logical capabilities and flows.
• Govern the enterprise AI landscape, demarcating developer-facing platforms from business applications.
• Lead technical design and implementation of AI enablement modules like AI Gateway and PI/PII detection pipelines.

Infrastructure Engineering & Compute Operationalisation:

• Own design and establishment of production-ready software layers for high-compute environments such as GPU infrastructure.
• Architect cloud-native multi-region endpoints across AWS, Azure, and GCP.
• Define standards for data and context layer integration using specialized databases.
• Develop structured agentic architecture balancing delivery speed with compliance and safety.

Governance, Traceability & Security:

• Enforce enterprise invocation standards with Correlation, Trace, and Span IDs across the AI Gateway.
• Author technical pre-deployment sign-offs and governance for autonomous and embedded agents.
• Collaborate with AI Risks & Ethics team to ensure compliance with security and privacy frameworks.

Technical Leadership & Ecosystem Influence:

• Lead AI Architecture Network, facilitating capability reviews and architecture discussions.
• Validate technical aspects for strategic partners ensuring license and data residency compliance.

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