3 days ago
Bengaluru, IndiaSenior
Responsibilities
- Design, build, automate, monitor, and optimize AWS AI/ML infrastructure for reliable, scalable, and cost-effective workloads.
- Write, review, and debug code, scripts, infrastructure-as-code, automation, monitoring, and deployment tooling.
- Configure GPU-enabled compute, Amazon EC2, Amazon EKS, Amazon SageMaker, and supporting storage and networking services.
- Support deployment automation and CI/CD pipelines using Git, Terraform or CloudFormation, Docker, Kubernetes, and workflow orchestration tools.
- Deploy and operate AI services, model-serving components, and data pipelines while applying reliability, security, scalability, and cost-efficiency practices.
- Monitor infrastructure and model-serving health with AWS CloudWatch and troubleshoot compute, storage, networking, container, and application issues.
- Collaborate with data scientists, ML engineers, platform engineers, and architects to integrate models into enterprise systems.
- Document reusable infrastructure patterns, configuration standards, and operational runbooks.
Requirements
- Minimum five years of experience is required.
- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related engineering field.
- At least two years of experience coding, building, monitoring, or troubleshooting AI/ML infrastructure, data platforms, model deployment pipelines, or cloud/platform engineering solutions.
- At least two 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 for AI workloads.
- Hands-on experience with AWS services including EC2, EKS, SageMaker, S3, IAM, VPC, CloudWatch, and related DevOps services.
- Experience with GPU or accelerated compute, distributed training, containerized deployments, model serving, infrastructure-as-code, Kubernetes, workflow orchestration, and operational monitoring.
- Understanding of MLOps patterns including experiment tracking, model registries, deployment, monitoring, and rollback.
- AWS certification and familiarity with LLM infrastructure, vector databases, retrieval pipelines, GPU scheduling, model optimization, security controls, FinOps, incident management, and production support are preferred.
Categories
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.