1 day ago
Bengaluru, IndiaStaff+
Responsibilities
- Set the Azure AI infrastructure vision, strategy, reference architecture, standards, and implementation approach for large-scale AI/ML systems.
- Design and optimize GPU-accelerated compute, distributed training environments, model-serving platforms, networking, storage, orchestration, and observability.
- Evaluate Azure services, AI infrastructure technologies, accelerators, managed services, vendors, and architecture alternatives.
- Define infrastructure-as-code, CI/CD, model deployment, monitoring, SLA/SLO, security, resilience, and cost/performance governance patterns.
- Lead architecture assessments and design reviews, validating solutions through prototyping, benchmarking, profiling, performance tuning, and troubleshooting.
- Provide executive and client-level technical advisory connected to business outcomes.
- Lead AI infrastructure projects and teams, mentor architects, and establish community best practices.
Requirements
- A bachelor’s degree in Computer Science, Computer Technical Architecting, Information Technology, or a related technical field is required.
- A minimum of 15 years of experience is required; the role also specifies at least 6 years building, designing, operating, monitoring, and troubleshooting AI/ML infrastructure or related large-scale architecture solutions.
- At least 6 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash, or PowerShell is required.
- Expert hands-on experience with Azure VMs, Azure Kubernetes Service, Azure Machine Learning, Azure Storage, Azure Virtual Network, Entra ID, Azure Monitor, and Azure DevOps or GitHub Actions is required.
- Strong knowledge of GPU and accelerated compute, distributed training, model serving, container platforms, storage and network design, observability, resilience, and infrastructure cost optimization is required.
- Experience with Apache Airflow, Kubeflow, managed orchestration services, or platform-native workflow tooling is required.
- Strong experience with Bicep, ARM, Terraform, CI/CD, Docker, Kubernetes, security guardrails, monitoring, MLOps, and InfraOps practices is required.
- Proven experience leading AI infrastructure projects and teams, evaluating technologies and reference architectures, conducting design reviews, and aligning stakeholders is required.
- Preferred qualifications include Azure certifications, industry experience in regulated or enterprise sectors, exposure to LLM infrastructure and vector databases, and experience with enterprise governance, roadmaps, vendor management, FinOps, and production support models.
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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.