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SeniorFull-timeKubernetesDockerTerraformCI/CDAI
Salary Range
$53,040 - $71,760 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
Join the AI Initiatives team as a Site Reliability Engineer and help operate, scale, and evolve the foundation that powers AI products across the company. This role sits within the AI team and focuses on ensuring that AI platforms, services, and agent-based systems are reliable, scalable, observable, and secure in production.
Key Responsibilities
- →Build and operate reliable AI infrastructure
- →Design, deploy, and operate cloud-native infrastructure supporting AI workloads, including LLM services, RAG pipelines, agent-based systems, and internal AI platforms
- →Develop automation, tooling, and services to support CI/CD, deployment, configuration, and lifecycle management of AI systems
- →Define and manage infrastructure using Infrastructure as Code (e.g. Terraform, CloudFormation), and build automation for provisioning, scaling, recovery, and routine operations
- →Design and maintain observability solutions (monitoring, logging, tracing, alerting) to ensure high availability, fast detection of issues, and effective incident response for AI services
- →Partner with AI engineers and product teams to review system designs, identify reliability risks, define SLOs/SLIs, and improve fault tolerance, scalability, and resilience of AI-powered systems
- →Operate and evolve containerized platforms using Docker and Kubernetes; support safe and frequent deployments through robust CI/CD pipelines
- →Develop an understanding of AI-specific operational challenges such as model serving, LLM latency, rate limits, cost control, caching, retries, fallbacks, and data pipeline reliability
- →Work closely with AI engineers, software engineers, and product teams to ensure that reliability, operability, and scalability are first-class concerns throughout the product lifecycle
Requirements
- ✓Strong software engineering skills combined with deep experience in cloud infrastructure, DevOps practices, and system reliability
- ✓Genuine interest in AI systems and how they behave in real-world production environments
- ✓Experience with Infrastructure as Code tools like Terraform or CloudFormation
- ✓Experience with containerized platforms using Docker and Kubernetes
- ✓Experience with observability tools for monitoring, logging, tracing, and alerting
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