Associate Director - AI Infrastructure Architect (AI Factory)

Overview

Associate Director, AI Infrastructure Architect in the AI & HPC Engineering team within Novartis Cloud & Hosting Services. An individual contributor architecture role that defines the reference architecture and guardrails for AI workloads across Azure, AWS and private AI environments.

What you'll do

• Own the AI infrastructure reference architecture and standards governing training, fine-tuning, inference and retrieval-augmented patterns across public cloud and private AI hosting.
• Define the standard AI workload intake pattern, including architecture review criteria, data classification handling, environment selection and conditions for production go-live.
• Set guardrails for sensitive data, model access, prompt and inference logging, monitoring, resilience, retention and cost, in partnership with Security, Data Privacy and Quality.
• Design GPU and accelerator capacity patterns (shared pools, reservations, scheduling, quotas and burst to cloud) and support the associated capacity and cost models.
• Support qualification of AI platforms, regions and services for enterprise consumption together with AI & HPC Engineering and the public cloud architects.
• Define the MLOps and LLMOps reference chain: model registry, versioning, evaluation, deployment, drift and performance monitoring, and decommissioning.
• Maintain architecture decision records for AI platform choices, linking each to business value, risk posture and total cost of ownership.
• Advise business, research and Infrastructure Solution Delivery stakeholders on feasible AI infrastructure options and translate scientific and commercial requirements into technical designs.
• Track the AI infrastructure market, evaluate emerging accelerators, model-serving stacks and platform services, and bring credible innovation into the roadmap.
• Coach engineers and architects on AI infrastructure practice and act as a role model for the Novartis Values and Behaviours.

What you'll need

• 8+ years' experience in infrastructure, cloud, or platform architecture, with a strong track record of designing and supporting enterprise-scale technology solutions.
• Demonstrated expertise in building, deploying, and operating AI and machine learning infrastructure within production environments.
• Experience enabling AI solutions to transition from proof-of-concept stages into scalable, governed, and business-critical services.
• Strong knowledge of GPU and accelerator technologies, Kubernetes, container orchestration, and cloud-based AI platforms such as Azure and AWS.
• Hands-on experience with model serving, inference optimization, MLOps/LLMOps practices, and modern data and vector pipeline architectures.
• Solid understanding of identity and access management, observability, cost optimization (FinOps), and secure AI platform operations.
• Familiarity with Responsible AI principles, including explainability, auditability, logging, human oversight, and risk management controls.
• Excellent stakeholder management and communication skills, with the ability to explain complex AI infrastructure concepts to technical and non-technical audiences while driving collaboration across engineering, security, privacy, and business teams.

Nice to have

• Fluent English, written and spoken.
• Additional languages are an asset.

Details

• Location: Hyderabad (Office).