Sr. Spec. DDIT IES Cloud Engineering

MAJOR ACCOUNTABILITIES

• Architect and Design: Lead the design and architecture of an AWS-based AI infrastructure platform, with a focus on supporting Generative AI workloads and advanced analytics for pharma business use-cases.
• Platform Development: Develop and deploy scalable AI solutions, leveraging AWS’s suite of services, including AWS Bedrock, Q, SageMaker, App Studio and AI Infrastructure tools.
• Data Management: Oversee the design and implementation of data storage, retrieval, and processing pipelines, ensuring the efficient handling of large datasets, including genomic and chemical compound data.
• Security and Compliance: In collaboration with cloud domain security architects, implement robust security measures and ensure compliance with relevant industry standards, particularly in handling business sensitive data.
• Collaboration: Work closely with data scientists, research scientists, and other business stakeholders to understand their needs and translate them into technical solutions.
• Performance Optimization: Optimize the performance and cost-efficiency of the platform, including monitoring and scaling resources as needed.
• Innovation: Stay updated with the latest trends and technologies in AI and cloud infrastructure, continuously exploring new ways to enhance the platform's capabilities.

Additional Specifications Required for the Position:

• Bachelor’s degree in Information Technology, Computer Science, or Engineering.
• AWS Solution Architect certification – professional
• 8+ years of strong technical hands-on experience of delivering infrastructure and platform services across geographic and business boundaries
• Minimum 5+ years’ of technical hands-on experience in AWS Solution Architect / Design Expert role for large enterprises
• Deep understanding of Architecture and Design of Platform Engineering products with focus mainly on Data science/ML compute products, Cognitive, (Gen)AI, etc.
• Extensive experience in building infra solutions on AWS, particularly with services like AWS Bedrock, Amazon Q, SageMaker, App Studio, Machine Learning and ECS/EKS
• Proficiency in AI and Machine Learning frameworks (TensorFlow, PyTorch, Keras) and familiarity with model deployment and operationalization (MLOps).
• Solid hands-on experience in Generative AI techniques, including Natural Language Processing (NLP), Generative Adversarial Networks (GANs), and transformer models.
• Good understanding of data engineering, including ETL processes, data warehousing, and working with both structured and unstructured data.
• Knowledge of containerization and orchestration technologies, such as Docker and Kubernetes.
• Experience with DevOps practices and tools, including CI/CD pipelines, infrastructure as code (IaC), and monitoring solutions.
• Excellent skills in collaborating with business users, Product team, Operationalizing the delivered products, working closely with Security for implementing compliance, close interaction with Cloud operations team for provisioning Azure services.
• Good knowledge on implementing well defined & industry standard Change management process for platform & its products. Have a well-structured Use-case onboarding process. Should ensure to have documentation for Platform products and implementations done.
• Experience with DevOps Orchestration/Configuration/Continuous Integration Management technologies
• Good understanding of High Availability and Disaster Recovery concepts for infrastructure
• Ability to analyze and resolve complex infrastructure resource and application deployment issues.

KEY PERFORMANCE INDICATORS / MEASURES OF SUCCESS

• Adherence to the Novartis IT quality standards
• Deliver on time
• Cost optimization
• Completeness and quality of deliverables
• Customer feedback (expectations met/exceeded)
• Application on boarding delivery success
• Actively contribute to the business with innovative solutions that show results in the form of cost optimization and / or growth of the business top line revenue.