AI Infrastructure Architect
Remote • Coimbatore
Posted 14h ago
About the job
As a Technical Architect in AI Infrastructure Architecture, you will act as a senior technical authority for AWS-based AI/ML compute infrastructure, shaping the technical vision, reference architecture, standards, and implementation strategy for large-scale AI systems. You will evaluate complex choices across compute, networking, storage, orchestration, model serving, observability, security, and cost optimization, while guiding senior and lead architects to deliver resilient, scalable, and production-ready AI infrastructure. You will bring industry experience across enterprise AI adoption, compliance, reliability, FinOps, and platform modernization to help clients translate AI infrastructure trade-offs into measurable business value.
Responsibilities
- Set the overarching AWS AI infrastructure vision, strategy, and reference architecture for large-scale AI/ML systems.
- Own complex architectural decisions across AWS services, rationalizing options against client standards and business objectives.
- Architect and prototype cost-optimized GPU/accelerated compute and distributed training environments.
- Define architecture standards, reusable infrastructure-as-code patterns, CI/CD approaches, model deployment patterns, monitoring strategy, SLAs/SLOs, and cost/performance governance.
- Lead architecture assessments and design reviews, validating findings through hands-on implementation, profiling, performance tuning, and troubleshooting.
- Evaluate emerging AI infrastructure technologies, accelerators, interconnects, managed AI services, and ecosystem tools.
- Provide executive and client-level technical advisory, translating cloud infrastructure trade-offs into clear, defensible recommendations.
- Mentor architects and build community best practices.
- Advise on AI infrastructure technology and vendor evaluation, selection, and full stack integration.
Requirements
- Minimum 6 years of experience coding, building, monitoring, troubleshooting, designing, and operating AI/ML infrastructure, cloud platforms, data platforms, model deployment pipelines, or large-scale solutions.
- Strong understanding of AI/ML concepts and the compute, infrastructure, orchestration, and deployment foundations required to run production AI systems.
- Minimum 6 years of proficiency in programming or scripting languages such as Python, Java, C++, Bash, or PowerShell.
- Experience with data pipeline and workflow management tools such as Apache Airflow or Kubeflow.
- Proven experience leading AI infrastructure projects and teams.
- Strong project management, communication, problem-solving, and cross-functional collaboration skills.
- Demonstrated experience evaluating and selecting AI technologies, frameworks, reference architectures, and platform services.
- Expert-level hands-on architecture experience with AWS AI infrastructure services including EC2, EKS, SageMaker, S3, IAM, VPC, CloudWatch, and automation/DevOps services.
- Deep knowledge of GPU/accelerated compute, distributed training, model serving, container platforms, storage design, network design, observability, and resilience.
- Strong experience with Terraform/CloudFormation, CI/CD, Docker, Kubernetes, security guardrails, monitoring, and infrastructure cost optimization.
- Ability to evaluate multiple AWS architecture options and produce standards, patterns, decision records, benchmarks, and executive-ready recommendations.
- Experience applying MLOps/InfraOps practices for experiment tracking, model registry, deployment automation, monitoring, incident response, and rollback strategies.
- Bachelor's degree in Computer Science, Computer Technical Architecting, Information Technology, or a related field.