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.