3 days ago
Coimbatore, IndiaSenior
Responsibilities
- Design, build, automate, monitor, and optimize AI/ML infrastructure on Microsoft Azure.
- Write, review, and debug code, scripts, and infrastructure-as-code for Azure AI infrastructure, automation, monitoring, and deployment tooling.
- Configure Azure VMs, Azure Kubernetes Service, Azure Machine Learning compute, Azure Storage, networking, and security services for AI/ML workloads.
- Support deployment automation and CI/CD pipelines using Git, Bicep/ARM, Terraform, Azure DevOps, GitHub Actions, Docker, Kubernetes, and workflow orchestration tooling.
- Deploy and operate AI services, model-serving components, and data pipelines with emphasis on reliability, security, scalability, and cost efficiency.
- Monitor infrastructure and model-serving health with Azure Monitor, Log Analytics, and related observability tools, troubleshooting issues across compute, storage, networking, containers, and application layers.
- Collaborate with data scientists, ML engineers, platform engineers, and architects to integrate AI models into enterprise systems.
- Document reusable infrastructure patterns, configuration standards, and runbooks for Azure-based AI platforms.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related engineering field.
- Minimum 5 years of experience is required; the qualifications also specify at least 2 years working with AI/ML infrastructure, data platforms, model deployment pipelines, or cloud/platform engineering solutions.
- At least 2 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash, or PowerShell.
- Strong understanding of AI/ML concepts and the compute, storage, networking, security, and deployment foundations required for AI workloads.
- Hands-on experience with Azure VMs, AKS, Azure Machine Learning, Azure Storage, Azure Virtual Network, Azure Monitor, Log Analytics, and Azure DevOps or GitHub Actions.
- Experience with CI/CD, infrastructure-as-code, containers, Kubernetes, workflow orchestration, operational monitoring, GPU or accelerated compute, distributed training, containerized deployments, and model serving.
- Working knowledge of Bicep/ARM, Terraform, Docker, Kubernetes, observability, and MLOps patterns including experiment tracking, model registry, deployment, monitoring, and rollback.
- Ability to optimize infrastructure for performance, reliability, scalability, cost, and security.
- Preferred qualifications include an Azure Administrator, Azure Developer, Azure Solutions Architect, Azure AI Engineer, or Azure Data Engineer certification; experience with enterprise AI use cases, large language model infrastructure, vector databases, retrieval pipelines, GPU scheduling, model optimization, security controls, FinOps, incident management, or production support.
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About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.