Site Reliability Engineer - AI Agents

You will be responsible for designing, operating, and scaling the infrastructure layer that powers AI agent systems in production, ensuring reliability, observability, and developer usability across the platform.

• Design, build, and operate scalable cloud infrastructure supporting AI agent execution, orchestration, and model serving in production


• Ensure reliability, performance, and observability of distributed agentic systems across internal and external products


• Develop platform services, APIs, SDKs, and self-service tooling to enable efficient consumption of AI infrastructure


• Manage compute, orchestration, and deployment infrastructure supporting AI and ML workloads at scale


• Build and maintain CI/CD pipelines for reliable, automated deployment of AI services and agent workflows


• Implement Infrastructure as Code using tools such as Terraform to provision and manage AWS environments


• Design and operate monitoring, logging, alerting, and incident response systems tailored to AI/ML workloads


• Define reliability patterns, guardrails, and failure recovery mechanisms for LLM and agent-based systems


• Collaborate with AI and Data Engineering teams to evolve experimental prototypes into production-grade systems


• Manage Kubernetes-based container orchestration environments for scalable deployment of services


• Implement security controls, access management, and infrastructure best practices across systems


• Document architecture, runbooks, and operational procedures to support platform adoption and reliability

Requirements

The ideal candidate is a strong SRE or platform engineer with experience in cloud-native systems, production infrastructure, and exposure to ML or AI-driven workloads.

• 5+ years of experience in Site Reliability Engineering, Platform Engineering, Infrastructure Engineering, or similar roles in production environments


• Hands-on experience supporting ML infrastructure, model serving, or MLOps pipelines in production


• Experience building developer platforms, internal tools, APIs, or SDKs used at scale by engineering teams


• Strong understanding of platform engineering principles, including self-service infrastructure and developer experience design


• Proficiency with Infrastructure as Code tools, particularly Terraform


• Strong experience with Kubernetes and containerized systems (Docker)


• Solid cloud infrastructure experience, preferably AWS


• Strong scripting and programming skills (Python preferred, plus bash/shell proficiency)


• Experience designing and operating observability, monitoring, and alerting systems


• Experience with incident response processes and on-call operational ownership


• Strong collaboration skills across AI, data, and engineering teams


• High ownership mindset with ability to operate in fast-paced, high-stakes production environments


• Familiarity with AI agent systems, LLM-based applications, or orchestration frameworks is a strong plus

Benefits

• Competitive compensation package with performance-based incentives


• Fully remote-friendly structure with flexibility across eligible regions


• Comprehensive health coverage including medical, dental, and vision (where applicable)


• Retirement savings plans with employer contributions (where applicable)


• Flexible PTO policy and paid company holidays


• Mental health and wellness support programs


• Learning and development budget for continuous technical growth


• Opportunity to work on cutting-edge AI agent infrastructure at global scale


• High-ownership engineering culture with strong cross-functional collaboration


• Exposure to advanced platform engineering and applied AI systems.