Senior Specialist, Platform Analytics AI ( Python and AWS)

Summary The Senior Specialist, Analytics AI role is responsible for the design, development, automation, and operational support of enterprise AI, GenAI, and MLOps platform capabilities. The role partners with business, architecture, security, data science, and engineering teams to deliver scalable, secure, and compliant AI platform services that accelerate the adoption of AI solutions across Novartis.

• Manage the end-to-end lifecycle of platform services including onboarding, provisioning, deployment, upgrades, support, monitoring, compliance, and retirement, ensuring reliable and governed operations.
• Partner with business, data, engineering, architecture, and security teams to translate complex business needs into platform capabilities, accelerating AI adoption and delivery of business value.
• Lead the implementation and governance of enterprise AI, data, and metadata management practices, ensuring secure, compliant, and trusted access to platform services and assets throughout their lifecycle.
• Demonstrate high agility in working across diverse business domains and technology landscapes, effectively communicating technical strategies, platform roadmaps, and business impact through executive presentations, dashboards, and storytelling.

About The Role Major Accountabilities

• Design, develop, and support scalable AI, GenAI, and Agentic AI platform capabilities that enable enterprise AI use cases.Build and operate MLOps, LLMOps, and AgenticOps capabilities to support model development, deployment, monitoring, and lifecycle management.
• Develop reusable platform services including model serving, inference services, orchestration frameworks, APIs, observability, and automation capabilities.Design and implement cloud-native AI platform solutions leveraging AWS services and enterprise cloud platforms. Enable and support enterprise AI services including foundation models, agent-based workflows, model inference, and AI automation capabilities.
• Develop and maintain platform APIs and automation services that enable self-service provisioning, deployment, and lifecycle management of AI resources. Drive platform automation across CI/CD pipelines, infrastructure provisioning, environment management, and deployment workflows.
• Design, implement, and support Databricks-based ML and GenAI workflows, including MLflow, model serving, and workflow automation. Collaborate with data scientists, engineers, architects, security teams, and business stakeholders to deliver scalable and reusable platform solutions.
• Support platform onboarding, deployment, migration, upgrade, and release activities while ensuring service continuity and operational stability. Ensure platform solutions comply with enterprise security, governance, quality, validation, and compliance requirements.
• Implement monitoring, observability, incident management, and operational support processes to maintain platform reliability and performance. Evaluate emerging AI, cloud, automation, and platform technologies to enhance platform capabilities and engineering productivity.
• Develop and maintain technical documentation, reference architectures, implementation standards, operational procedures, and user guidance. Act as a technical subject matter expert for platform capabilities and provide support for complex platform and cloud engineering challenges.
• Proactively identify technical risks, dependencies, and operational issues and drive them to resolution in collaboration with relevant stakeholders. Communicate technical solutions, recommendations, and implementation approaches effectively to technical and non-technical audiences.
• Partner with vendors and internal technology teams to evaluate platform capabilities and support continuous platform improvement initiatives. Ensure adherence to Novartis quality, security, risk management, and regulatory standards across all platform services and solutions. Contribute to a culture of innovation, automation, operational excellence, and continuous improvement within the AI Platform Engineering function.

Minimum Requirements

• Experience in AI/ML Platform Engineering, MLOps, Platform Engineering, Cloud Engineering, or related software engineering disciplines.
• Strong hands-on experience with AWS cloud services and cloud-native architecture patterns.
• Experience with AWS Bedrock, Bedrock AgentCore, SageMaker, Databricks, MLflow, or equivalent AI platform technologies.
• Strong programm…