Site Reliability Engineer (5757)

Role overview Design, automate, and operate cloud platforms that support compute-intensive AI and machine learning workloads. This mid-level site reliability role combines hands-on infrastructure engineering with customer-facing technical consultation across commercial, private, hybrid, and government cloud environments.

Responsibilities - Build and maintain highly available Kubernetes clusters for AI and ML training, inference, and GPU use. - Consult with customer stakeholders to understand requirements, explain technical options, and support solution demonstrations and scoping. - Partner with delivery and account teams to validate architectures for AI/ML platforms and secure software delivery. - Automate infrastructure with Terraform or comparable tools and Git-based workflows, incorporating security controls and compliance safeguards. - Create resilient CI/CD pipelines with container vulnerability scanning, artifact tracking, and audit logs. - Monitor capacity and platform health, participate in on-call support, investigate root causes, and document operational lessons. - Produce technical diagrams, reference architectures, runbooks, and client handoff materials.

Requirements - 3–5 years of experience in site reliability, DevOps, or platform engineering. - Strong Kubernetes operations skills, including networking, role-based access control, pod security, and secrets management. - Practical experience managing infrastructure on a major cloud platform, including networking, identity, encryption, security, and logging. - Experience with Terraform or equivalent infrastructure-as-code tools and Git workflows. - Proficiency in Python, Bash, or Go for automation and tooling. - Ability to explain infrastructure clearly to customers, troubleshoot across compute, storage, networking, and application layers, and apply security baselines such as CIS or NIST concepts.

Nice to have - Experience operating infrastructure for AI/ML workloads or in government and regulated cloud environments. - Familiarity with hybrid, multi-cloud, or private cloud architectures and observability tools such as Prometheus, Grafana, Splunk, or Datadog. - Relevant cloud or cloud-native certifications.

Benefits and work setup - Fully remote position open to candidates in the United States. - Benefits include health insurance, paid leave, retirement, and learning and development opportunities.