3 days ago
Bengaluru, IndiaSenior
Responsibilities
- Design, build, automate, monitor, and optimize AWS AI/ML infrastructure for scalable and reliable model development and production workloads.
- Write, review, and debug code, scripts, and infrastructure-as-code for infrastructure automation, monitoring, and deployment tooling.
- Configure GPU-enabled AWS compute, including Amazon EC2, Amazon EKS, Amazon SageMaker, and supporting storage and networking services.
- Support deployment automation and pipelines using Git, Terraform or CloudFormation, Docker, Kubernetes, and workflow orchestration tooling.
- Deploy and operate AI services, model-serving components, and data pipelines while optimizing reliability, security, scalability, performance, and cost.
- 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 AI models into enterprise systems.
- Document reusable infrastructure patterns, configuration standards, and operational runbooks.
Requirements
- At least five years of overall 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 Python, Java, C++, Bash, or PowerShell.
- Strong understanding of AI/ML concepts and the compute, storage, networking, security, and deployment foundations needed to run AI workloads.
- Experience with AWS AI infrastructure services, GPU or accelerated compute, distributed training, containerized deployments, model serving, infrastructure-as-code, Kubernetes, CI/CD pipelines, workflow orchestration, and observability.
- Understanding of MLOps practices 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 enterprise 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.