Jobs at Novartis

Sr Spec DDIT IES cloud Engineer will be responsible for designing, engineering, implementing, and operating enterprise AI infrastructure and platform capabilities that enable secure, scalable, and governed adoption of AI technologies across the enterprise.

The role will focus on engineering enterprise AI platforms, developer environments, infrastructure, automation, and enterprise integrations across SaaS AI platforms, cloud AI services, hybrid, and on-premises environments. The role will collaborate with Enterprise Architecture, Hybrid Infrastructure, Security, Identity & Access Management, Networking, End User Computing, Operations, AI Enablement, and Business Technology teams.

• Design, engineer, deploy, and support enterprise AI infrastructure and platform capabilities.
• Onboard and integrate enterprise AI platforms with enterprise identity, networking, security, monitoring, and operational services.
• Engineer AI developer environments, AI workspaces, API connectivity, model access, and platform integrations.
• Develop reusable platform components, reference implementations, and engineering patterns to accelerate enterprise AI adoption.
• Develop Infrastructure as Code (IaC) solutions using Terraform, CFT, Bicep, ARM, Ansible, or equivalent technologies.
• Build and maintain CI/CD pipelines for provisioning, configuration, deployment, and lifecycle management of AI platforms.
• Automate infrastructure provisioning, platform operations, configuration management, and operational workflows using scripting and DevOps practices.
• Implement platform monitoring, logging, observability, backup, disaster recovery, high availability, and performance optimization solutions.
• Troubleshoot complex infrastructure, networking, platform, and integration issues across enterprise AI environments.
• Support operational excellence through proactive monitoring, incident resolution, and continuous service improvement.

Essential Requirements

• Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent practical experience.
• 5+ years of experience in AI Infrastructure Engineering, Cloud Engineering and DevOps toolsets
• Relevant Cloud, Kubernetes, DevOps, Security, or AI certifications.
• Experience engineering enterprise AI platforms supporting Generative AI and AI-enabled workloads.
• Understanding of LLMs, AI APIs, AI agents, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), vector databases, model access patterns, and enterprise AI platform architecture.
• Enterprise AI ecosystems such as ChatGPT Enterprise, Claude, Gemini, Azure AI Foundry, AWS Bedrock, AgentCore, Vertex AI, Strands Agents SDK, LangGraph, CrewAI, Run.AI or SLURM or open-source AI platforms.
• Kubernetes & Container Platforms
• Infrastructure as Code (IaC), DevSecOps & CI/CD

Desirable Requirements:

• AWS & Azure Monitor, Prometheus, Grafana, Log Analytics, Kusto Query Language (KQL), or equivalent monitoring platforms
• AI Developer Platforms (JupyterLab, VS Code, AI Workstations, Claude Cowork).