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Assoc. Dir. DDIT IES Cloud Engg., Azure AI

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Novartis

17d ago

  • Job
    Full-time
    Expert Level
  • Software Engineering
    IT & Cybersecurity
  • Hyderabad, +1

AI generated summary

  • You need a Bachelor’s in IT or related field, Azure Solution Architect certification, 10+ years in cloud, 5+ years in Azure roles, expertise in AI/ML, strong DevOps skills, excellent communication.
  • You will architect Azure-based AI platforms, develop scalable AI solutions, manage data pipelines, ensure security compliance, collaborate with stakeholders, optimize performance, and explore new technologies.

Requirements

  • Bachelor’s degree in Information Technology, Computer Science, or Engineering.
  • MS-Azure Solution Architect certification – professional level
  • 10+ years of solid experience working in public cloud environments; delivering infrastructure and platform services across geographic and business boundaries
  • Minimum 5+ years’ experience working in MS-Azure 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 Microsoft Azure, particularly with services like Azure OpenAI, AI Studio, Machine Learning, Azure Kubernetes Service (AKS), Azure Synapse Analytics, Azure Cognitive Services and Azure Data Lake.
  • 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 (e.g., GPT, BERT).
  • Good understanding in 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.
  • Excellent written, presentation and verbal communication skills
  • Languages: Fluent in English (written & spoken), additional languages a plus

Responsibilities

  • Architect and Design: Lead the design and architecture of an Azure-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 Azure’s suite of services, including Azure Machine Learning, Azure Synapse Analytics, and other relevant 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 requirements.
  • 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.
  • Multi-Cloud: Has good exposure/understanding of other Cloud and GenAI technologies like GCP, OpenAI, AWS, etc.

FAQs

What is the main responsibility of the Associate Director of DDIT IES Cloud Engineering, Azure AI?

The main responsibility includes designing and developing a cutting-edge AI and Generative AI infrastructure platform on Microsoft Azure cloud, specifically tailored for pharmaceutical business use-cases.

What qualifications are required for this position?

A Bachelor’s degree in Information Technology, Computer Science, or Engineering is required, along with an MS-Azure Solution Architect professional level certification and 10+ years of experience in public cloud environments.

How many years of experience in Microsoft Azure Solution Architect role are required?

A minimum of 5+ years’ experience working in an MS-Azure Solution Architect/Design Expert role for large enterprises is required.

What key Azure services should candidates be experienced with?

Candidates should have extensive experience with Azure services such as Azure OpenAI, AI Studio, Azure Machine Learning, Azure Kubernetes Service (AKS), Azure Synapse Analytics, Azure Cognitive Services, and Azure Data Lake.

Is familiarity with Generative AI techniques necessary for this role?

Yes, candidates should have solid hands-on experience in Generative AI techniques, including Natural Language Processing (NLP), Generative Adversarial Networks (GANs), and transformer models like GPT and BERT.

Are there any specific performance metrics for this position?

Yes, key performance indicators include adherence to IT quality standards, timely deliveries, cost optimization, quality of deliverables, customer feedback, successful application onboarding, and contribution to innovative solutions.

Is knowledge of data engineering important in this role?

Yes, a good understanding of data engineering, including ETL processes and working with structured and unstructured data, is important for this position.

What kind of collaboration is expected in this role?

Strong collaboration with data scientists, research scientists, and other business stakeholders is expected to understand their needs and translate them into technical requirements.

Are there specific DevOps practices and tools that are necessary for candidates to be familiar with?

Yes, candidates should have experience with DevOps practices and tools, including CI/CD pipelines, infrastructure as code (IaC), and monitoring solutions.

What languages are required for this job?

Excellent written, presentation, and verbal communication skills in English are required, and additional languages are a plus.

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Novartis

Science & Healthcare
Industry
10,001+
Employees

Mission & Purpose

Novartis is reimagining medicine to improve and extend people’s lives. As a leading global medicines company, we use innovative science and digital technologies to create transformative treatments in areas of great medical need. In our quest to find new medicines, we consistently rank among the world’s top companies investing in research and development. Novartis products reach nearly 800 million people globally and we are finding innovative ways to expand access to our latest treatments. Around 108,000 people of more than 140 nationalities work at Novartis around the world.

Culture & Values

  • Inspired

    Engage our people. Strive for patients. Live our purpose

  • Curious

    Learn. Be open. Be self-aware

  • Unbossed

    Create clarity. Serve others. Own your actions

  • Integrity

    Be honest. Have courage. Do what’s right